Seismic image filtering machine to generate a filtered seismic image, program products, and related methods

ABSTRACT

Seismic image filtering machines, systems, program products, and computer implemented methods are provided to generate a filtered seismic image responsive to filtered seismic image data generated by attenuating coherent seismic noise from surface waves of an unfiltered wavefield constructed from unfiltered seismic image data through a single downward extrapolation of the unfiltered wavefield using a plurality of nonstationary convolution operators to perform localized filtering at each of a plurality of spatial locations of the unfiltered wavefield. Various embodiments, for example, can beneficially handle strong lateral velocity variations thus making various embodiments effective tools to remove complicated coherent seismic noise which is typically in the form of exponentially decaying evanescent waves. Embodiments of the present invention, for example, can use, as a part of the filtering mechanism, specially designed nonstationary convolution operators that are implemented in the space-frequency domain as nonstationary filters.

RELATED APPLICATIONS

This application is a continuation application of and claims priority toU.S. patent application Ser. No. 13/681,207 titled “Seismic ImageFiltering Machine to Generate a Filtered Seismic Image, ProgramProducts, and Related Methods” and filed Nov. 19, 2012, which is acontinuation application of and claims priority to U.S. patentapplication Ser. No. 12/608,519, now U.S. Pat. No. 8,321,134, titled“Seismic Image Filtering Machine to Generate a Filtered Seismic Image,Program Products, and Related Methods” and filed Oct. 29, 2009, whichclaims priority to and claims the benefit of U.S. Provisional PatentApplication Ser. No. 61/110,214 titled “System and Program Product toAttenuate Coherent Seismic Noise from Surface Waves Using NonstationaryFilters and Associated Methods” and filed Oct. 31, 2008, all of whichare incorporated herein by reference in their entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention generally relates to the field of geophysical subsurfaceseismic imaging in the field of geophysical seismic exploration. Morespecifically, this invention generally relates to machines, programproducts, and methods to generate filtered seismic images based onseismic image data filtered by attenuating coherent noise fromunfiltered seismic image data using a plurality of nonstationaryconvolution operators as local filters at each spatial location of anunfiltered seismic image wavefield.

2. Description of Related Art

In the oil and gas industry, geophysical seismic data processing andanalysis techniques are commonly used to aid in the search for, andevaluation of, subterranean hydrocarbon deposits. In many instances, aseismic energy source can be used to generate seismic energy signalsthat propagate into the earth and are, at least partially, reflected bysubsurface seismic reflectors such as interfaces between undergroundformations having different acoustic impedances. Such seismic energyreflections can subsequently be recorded in a geophysical time series byseismic energy detectors, sensors, or receivers positioned at arecording surface located at or near the surface of the earth, in a bodyof water, or at known depths in boreholes. The resulting seismic datathen can be processed and analyzed to yield information relating to thelocation of the subsurface reflectors and the physical properties of thesubsurface formations.

Processed seismic data, in the form of surface waves delineating awavefield, can be useful in delineating and mapping the earth'ssubsurface features. Geophysical time series data acquired in the field,however, often contains undesired dispersive energy, such as coherentseismic noise, as well as desired seismic energy. Such unwanted coherentseismic noise can interfere with, overwhelm, or otherwise mask desiredseismic energy useful for subsurface explorations. Particularly, whenpropagating through an irregular surface or complex near surface, suchas, rugged topography or complex geology, surface waves can havecomplicated wave paths and lateral velocity variations resulting inunwanted dispersive energy. Much of this energy propagates horizontallyin the near surface of a wavefield. In the presence of complex geologyor rugged topography, this energy can have a complicated wave path, thusmaking its removal a challenging task. Nevertheless, removing thisdispersive energy is an important and beneficial step that is necessary,in many cases, to focus the subsurface seismic image so that it can beused for accurate and cost-effective subsurface exploration.

Current solutions attenuate unwanted dispersive energy and coherentseismic noise from seismic image data by downwardly continuing theseismic data wavefield through a data extrapolation to a depth levelbelow the propagation zone of the surface waves followed by an upwardcontinuation, or extrapolation of the data, back up to the seismic datarecording surface. Other current solutions attenuate noise by upwardlycontinuing the seismic image wavefield through a data extrapolation to adepth level above the highest elevation followed by a downwardcontinuation, or extrapolation of the data, back to the recordingsurface. Both approaches can be at least marginally effective (albeitinefficient) because the seismic imaging surface waves often manifestthemselves as evanescent waves which exhibit exponential decay withdistance and are therefore capable of being filtered out during thewavefield extrapolation.

SUMMARY OF THE INVENTION

Accordingly, as subsurface imaging becomes of even greater importance toenergy companies as they strive to tap the potential of more remotemineral deposits, applicants recognize a need for a more efficient andcomputationally inexpensive process for attenuating coherent seismicnoise from surface waves. Because previous methods require forward andinverse extrapolation of the data and the data must be sorted betweenthe source and receiver domains for each extrapolation, such previousmethods were recognized by applicants as inefficient and computationallyexpensive. Particularly, applicants recognize a need for variousmachines, systems, computer implemented methods, and program products togenerate a filtered seismic image based on filtered seismic image datathat has been filtered according to various embodiments of the presentinvention.

Generally, seismic imaging directs an intense sound from a seismicenergy source device into the ground to evaluate subsurface conditionsand to detect possible concentrations of oil, gas, and other subsurfaceminerals. Seismic image receiver devices, known as geophones, recordsound wave echoes that come back up through the ground to the recordingsurface. Such seismic image receiver devices, or geophones, can recordthe intensity of such sound waves and the time it took for the soundwave to travel from the sound source device back to the geophonerecording device at the recording surface. According to variousexemplary embodiments of the present invention, for example, during theseismic imaging process, the reflections of sound waves emitted by thesound source device, and recorded by the geophone recording device, canbe processed by a computer to generate a three-dimensional digitalmodel, or seismic image, of the subsurface. The three-dimensional modelof the subsurface can be used to identify, for example, the placement ofwells and potential well flow paths.

More specifically, according to an exemplary embodiment of the presentinvention, a seismic energy receiver can be positioned to receive andrecord seismic energy data or seismic field records in any formincluding a geophysical time series recording of the acoustic reflectionand refraction of waveforms that travel from the seismic energy sourceto the seismic energy receiver. Variations in the travel times ofreflection and refraction events in one or more field records in aplurality of seismic signals can, for example, when processed by acomputer, produce a seismic image, defined by unfiltered seismic imagedata, that demonstrates subsurface structure. The seismic image,however, is unfiltered and accordingly, it may, in many instances,contain not only seismic image data but also complicated coherentseismic noise in the form of evanescent waves as known and understood bythose skilled in the art. Such complicated coherent seismic noise withrespect to an unfiltered seismic image is similar to fuzz or grain on aimage taken with a film camera. By applying certain filters to the filmimage, it is possible, in many instances, to remove such fuzz or grain.The same is true for complicated coherent seismic noise present in anunfiltered seismic image. Accordingly, prior to using a seismic image toaid in the search for, and exploitation of, mineral deposits, theseismic image should first be filtered according to an exemplaryembodiment of the present invention.

According to various embodiments of the present invention, theunfiltered seismic image data can be filtered by attenuating coherentseismic noise from surface waves in a manner that requires fewerextrapolation processes and fewer sorting operations thereby resultingin a faster and more efficient attenuation of complicated coherentseismic noise. Such an advancement would beneficially allow energycompanies to explore greater regions of the subsurface terrain in a morecost effective manner thereby allowing such companies to find and obtainvast quantities of undiscovered oil and gas that could ultimately bedelivered to consumers at low cost. Computationally efficient seismicimage filtering, as provided through various embodiments of the presentinvention, may beneficially raise the supply of oil thereby lowering theprice at the pump for consumers worldwide.

In view of the foregoing, embodiments of the present inventionadvantageously provide, for example, seismic image filtering machines,systems, computer implemented methods, and computer readable programproducts, stored in a tangible computer readable storage medium, togenerate a filtered seismic image based on seismic image data filteredby attenuating coherent seismic noise from surface waves using aplurality of nonstationary convolution operators, as is known anunderstood in the art, as local filters that require only a singleextrapolation process, which can be implemented either in the source orreceiver domain, and which do not require sorting operations.Conceptionally, convolution, as is known and understood by those skilledin the art, can be described as the process of replacing each point ofdata of an unfiltered image by a scaled copy of a convolution filter.Commonly, convolution operators (or filters), as is known and understoodin the art, are stationary, meaning that the operator's form does notchange with space or time. While such stationary convolution operatorsaccurately filter more traditional images, a stationary convolutionoperator's inability to change its form with space or time (i.e.,velocity) is often too limiting to accurately filter geophysical seismicimages.

Particularly, unfiltered seismic image data can be used to construct, bya computer, an unfiltered wavefield including a plurality of waveletsand delineated by a plurality of spatial locations as is known andunderstood by those skilled in the art. The velocity of various spatiallocations within such an unfiltered wavefield can vary from spatiallocation to spatial location and as such, stationary convolutionoperators are unable to provide the needed flexibility. A mathematicalprocess which can form a scaled superposition of a filter while allowingthe wavelet radius to depend on a local velocity at a spatial locationof within a wavefield is known and understood by those skilled in theart as a nonstationary convolution. Beneficially, and unlike stationaryconvolution operators, nonstationary convolution operators according tovarious exemplary embodiments of the present invention can change form,for example, in a controlled fashion with time and space. That is,nonstationary convolution operators can beneficially be, for example,dependent on velocity measurements at various spatial locations of anunfiltered wavefield formed from unfiltered seismic image defined by aplurality of unfiltered seismic image data according to variousexemplary embodiments of the present invention. Thus, such nonstationaryconvolution operators can, for example, be used to filter an unfilteredseismic image to thereby generate a filtered seismic image.

Accordingly, various embodiments of the invention, for example, canbeneficially handle strong lateral velocity variations, thus makingvarious embodiments of the present invention effective tools to removecomplicated coherent seismic noise typically in the form ofexponentially decaying evanescent waves. Embodiments of the presentinvention, for example, use, as a part of the filtering mechanism,specially designed nonstationary convolution operators that areimplemented in the space-frequency domain as nonstationary filters.According to various embodiments of the present invention, suchnonstationary convolution operators can be constructed at each of theplurality of spatial locations of an unsorted wavefield so that each ofthe plurality of spatial locations of the unsorted wavefield can belocally filtered in a single extrapolation process.

Generally, according to exemplary embodiments of the present invention anonstationary seismic image data filter can be implemented in thespace-frequency domain to filter such seismic image data. Such anonstationary seismic image data filter can include, for example, anonstationary convolution operator designed using a weighted leastsquares with a transition band approach, as is known and understood bythose skilled in the art, that is configured to attenuate coherentseismic energy, or noise, from the seismic image. The nonstationaryseismic image data filter, according to various embodiments of thepresent invention, can operate by applying a nonstationary convolutionoperator to downwardly continue the unfiltered seismic image data to adepth level below a surface wave propagation zone of the seismic energy,as is known and understood by those skilled in the art, to therebyproduce filtered seismic image data that, when processed by a computerproduces a filtered seismic image on a display adapted to be incommunication with the computer. A display, according to variousembodiments of the present invention, can include a CRT monitor, a LCDmonitor, a plasma monitor, a OLED screen, a television, a DLP monitor, avideo projection, a three-dimensional projection, a touch screen, andany other graphical user interface device now or herein after developedas is known or understood by those skilled in the art.

Generally, images of various types, including both filtered andunfiltered seismic images, can be represented by a plurality of datapoints typically in the form of an image matrix as is known andunderstood by those skilled in the art. Such an image matrix can beprocessed and manipulated by a computer in order to produce ahuman-readable version of the image represented by the plurality ofimage data points on a display adapted to be in communication with thecomputer. Accordingly, embodiments of the present invention can, forexample, beneficially produce a filtered seismic image on a displayadapted to be in communication with a computer responsive to attenuatingcoherent seismic noise from an unfiltered seismic image using aplurality of nonstationary convolution operators as local filters.

Beneficially, for example, the nonstationary seismic image data filtercan filter the unfiltered seismic image through only a single downwardextrapolation process and without the need to sort the unfilteredseismic image data. When compared to other filter configurations whichrequire multiple data extrapolation processes and a sorted data set, theembodied filter enhances the speed and efficiency of current seismicfilters by reducing the process steps necessary to filter a seismicimage. Additionally, the nonstationary seismic image data filter canhandle strong lateral velocity variation thereby making it an effectivetool to remove complicated coherent noise due to complex geology orrugged topography. Generally, the nonstationary seismic image datafilter can be, for example, derived from the space-frequency explicitwavefield extrapolation imaging algorithm. At each lateral spatiallocation, the velocity information of the seismic energy signal can beused to build nonstationary convolution operators which performlocalized filtering in the space-frequency domain. Such a configuration,according to exemplary embodiments of the present invention, can use thesame velocity model used for resolving near surface distortions.

According to exemplary embodiments of the present invention, a pluralityof seismic signals can be generated using a seismic energy source thatpropagates into the earth and is at least partially reflected bysubsurface seismic reflectors, such as interfaces between undergroundformations having different acoustic impedances. The reflections andrefractions of the seismic signals can be received by one or moresensors and recorded by a computer or data processor in geophysical timeseries by seismic energy receivers located at or near the surface of theearth, in a body of water, or at known depths in boreholes. The recordedseismic signals can then, for example, be converted into unfilteredseismic image data. The unfiltered seismic image data can, whenprocessed by a computer, for example, produce an unfiltered seismicimage on a display adapted to be in communication with the computer. Theplurality of unfiltered seismic image data can then, according toexemplary embodiments of the present invention, be transmitted to anonstationary seismic image data filter implemented in thespace-frequency domain where the unfiltered seismic image data can beextrapolated to create new filtered seismic image data by applying anonstationary convolution operator to downwardly continue the unfilteredseismic image data to a depth level below a surface wave propagationzone as is known and understood by those skilled in the art. Thenonstationary convolution operator, for example, can be designed using aweighted least-squares with a transition band approach as is known andunderstood by those skilled in the art. The new filtered seismic imagedata can be subsequently processed by a computer and provided to adisplay adapted to be in communication with the computer such that afiltered seismic image is displayed on the display responsive to aseismic image filtering process according to various exemplaryembodiments of the present invention.

Beneficially, for example, the nonstationary seismic image data filtercan filter the unfiltered seismic image through only a single downwardextrapolation process and without the need to sort the unfilteredseismic image data. Other filter configurations, for example, requiremultiple data extrapolation processes and a sorted data set. A filter ofthis embodiment, for example, enhances the speed and efficiency ofcurrent seismic filters by reducing the process steps necessary tofilter the data. Accordingly, embodiments of the present invention, forexample, achieve greater efficiency than other methods while stillproducing a high-quality, accurate, filtered seismic image.

More particularly, an exemplary embodiment of the present inventionprovides a seismic image filtering machine to create a filtered seismicimage responsive to filtered seismic image data generated by attenuatingcoherent seismic noise from surface waves of an unfiltered wavefieldconstructed from unfiltered seismic image data through a single downwardextrapolation using a plurality of nonstationary convolution operatorsto perform localized filtering at each of a plurality of spatiallocations of the unfiltered wavefield. Such a seismic image filteringmachine, according to an exemplary embodiment of the present invention,can beneficially include a database configured to store unfiltered,unsorted seismic image data, a computer adapted to be in communicationwith the first database and having at least a processor and memory, andvarious computer readable program products stored in tangible computerreadable storage mediums. According to an exemplary embodiment of thepresent invention, the unfiltered, unsorted seismic image data can bederived from a plurality of seismic energy signals received from aseismic energy receiver at a recording surface once such signals havepropagated throughout a surface wave propagation zone as is known andunderstood by those skilled in the art.

Furthermore, according to various embodiments of the present invention,the aforementioned various computer readable program products canbeneficially include, for example, an unfiltered wavefield constructorcomputer readable program product, a nonstationary convolution operatorbuilder computer readable program product, a localized filter computerreadable program product, and a filtered seismic image creator computerreadable program product. The unfiltered wavefield constructor computerreadable program product can be stored in a tangible computer readablestorage medium and can, for example, include instructions that, whenexecuted by the computer, cause the computer to perform the operation ofconstructing an unfiltered wavefield delineated by a plurality ofspatial locations from the unfiltered, unsorted seismic image datastored in the first database. Additionally, the nonstationaryconvolution operator builder computer readable program product, caninclude, for example, instructions that when executed by the computer,cause the computer to perform the operation of building, responsive tothe unfiltered wavefield constructer computer readable program product,a plurality of nonstationary convolution operators, one for each of theplurality of spatial locations of the unfiltered wavefield. Each of thenonstationary convolution operators can be beneficially based, forexample, on the coordinate location of each of the plurality of spatiallocations of the unfiltered wavefield and the space-variant velocity,temporal frequency, transverse wavenumber, and wavelength of theunfiltered wavefield at each spatial location.

Also, according to an exemplary embodiment of the present invention, thelocalized filter computer readable program product can beneficiallyinclude instructions that, when executed by the computer, cause thecomputer to perform the operation of locally filtering each of theplurality of spatial locations of the unfiltered wavefield using, ateach spatial locations, at least one of the plurality of nonstationaryconvolutions operators associated with that one of the plurality ofspatial locations to thereby effectuate a single downward extrapolationof the unfiltered wavefield. Moreover, the filtered seismic imagecreator computer readable program product can include, for example,instructions that, when executed by the computer, cause the computer toperform the operation of creating a filtered seismic image responsive tofiltered seismic image data generated by the localized filter computerreadable program product at each of the plurality of spatial locationsof the unfiltered wavefield.

Such a seismic image filtering machine, according to an exemplaryembodiment of the present invention, can further beneficially include anonstationary convolution operator stabilizer computer readable programproduct stored in a tangible computer readable storage medium andincluding instructions that, when executed by the computer, cause thecomputer to perform the operation of stabilizing each of thenonstationary convolution operators using a weighted least squares witha transition band approach. Additionally, so mineral explorers canbetter interpret, use, and study the filtered seismic image generated bysuch a seismic image filtering machine, the seismic image filteringmachine can beneficially include, for example, a display and a filteredimage displayer computer readable program product stored in a tangiblecomputer readable storage medium and including instructions that, whenexecuted by the computer, cause the computer to perform the operation ofdisplaying the filtered seismic image on the display responsive toconverting the filtered seismic image data into a graphic image capableof being displayed on the display in human-readable form.

Moreover, so that both unfiltered and filtered seismic data can bebeneficially preserved for any desired future analysis or investigation,the seismic image filtering machine can further include a seconddatabase, a third database, and a fourth database, each adapted to be incommunication with the computer. The unfiltered wavefield constructorcomputer readable program product can include instructions, for example,that when executed by the computer, cause the computer to perform theoperation of storing the unfiltered wavefield in the second database.Also beneficially, the localized filter computer readable programproduct can further includes instructions that, when executed by thecomputer, cause the computer to perform the operation of storing the oneor more filtered seismic image data in the third database. Additionally,the filtered seismic image creator computer readable program product canfurther include, for example, instructions that, when executed to thecomputer, cause the computer to perform the operation of storing thefiltered seismic image in the fourth database.

Another exemplary embodiment of the present invention provides, by wayof example, a computer implemented method to generate a filtered seismicdata image based on filtered seismic image data by attenuating coherentseismic noise from surface waves through a single downward extrapolationusing specially-constructed nonstationary convolution operators toperform localized filtering at each of a plurality of spatial locationsof an unfiltered wavefield. According to such an exemplary embodiment ofthe present invention, the computer implemented method can include, forexample, the step of constructing by a computer in a first computerprocess an unfiltered wavefield delineated by a plurality of spatiallocations of unfiltered, unsorted seismic image data based on aplurality of seismic energy signals propagated through a surface wavepropagation zone received from a seismic image receiver, as is known andunderstood by those skilled in the art. Moreover, such a computerimplemented method, can also include the step of building, by thecomputer in a second computer process, a plurality of nonstationaryconvolution operators, one for each of the plurality of spatiallocations of the unfiltered wavefield, responsive to constructing theunfiltered wavefield in the first computer process for each of theplurality of spatial locations of the unfiltered wavefield.Beneficially, each of the nonstationary convolution operators can bebased on the coordinate location of each of the plurality of spatiallocations of the unfiltered wavefield within the unfiltered wavefield,and the space-variant velocity, temporal frequency, transversewavenumber, and wavelength of the unfiltered wavefield at each spatiallocation. To even further increase the efficacy of such nonstationaryconvolution operators, computer implemented methods, according tovarious exemplary embodiments of the present invention, can furtherinclude the step of stabilizing, in a computer process by the computer,each of the nonstationary convolution operators built for each of theplurality of spatial locations of the unfiltered wavefield using aweighted least squares with a transition band approach.

Responsive to the step of building a plurality of nonstationaryconvolution operators, such a computer implemented method can alsoinclude, for example, the step of extrapolating, by the computer in athird computer process, the unfiltered wavefield at each of theplurality of spatial locations of the unfiltered wavefield to a depthlevel below the surface wave propagation zone of the seismic energysignals, as is known and understood by those skilled in the art. Thestep of extrapolating, for example, can beneficially use, at each of theplurality of spatial locations, at least one of the plurality ofnonstationary convolution operators built by the computer in the secondcomputer process associated with that one of the plurality of spatiallocations, to thereby locally filter each of the plurality of spatiallocations of the unfiltered wavefield. Furthermore, a computerimplemented method according to an exemplary embodiment of the presentinvention can include the step of generating, by the computer in afourth computer process, a filtered seismic image by processing theunfiltered, unsorted seismic image data associated with each of theplurality of spatial locations of the unfiltered wavefield locallyfiltered by the computer in the third computer process to therebygenerate filtered seismic image data that when further processed by thecomputer generates a filtered seismic image on a display adapted to bein communication with the computer.

Computer implemented methods according to various exemplary embodimentsof the present invention can further beneficially include the step ofgenerating filtered seismic image data responsive to extrapolating, bythe computer in the third computer process, the unfiltered wavefield ateach of the plurality of spatial locations of the unfiltered wavefield.Accordingly, according to an exemplary embodiment of the presentinvention, the filtered seismic image generated by the computer in thefourth computer process can be beneficially based on such filteredseismic image data. Such computer implemented methods can even furtherinclude, for example, the steps of receiving from a seismic imagereceiver at a recording surface a plurality of seismic energy signalsthat have propagated throughout a surface wave propagation zone, as isknown and understood by those skilled in the art, and converting theplurality of seismic energy signals received from the seismic energyreceiver into unfiltered, unsorted seismic image data.

Similarly to various seismic imaging filtering machines according tovarious exemplary embodiments of the present invention, both filteredseismic image data and unfiltered seismic image data can be stored indatabases for future review, investigation, and analysis by subsurfaceexplorers, seismic imaging experts, oil and gas professionals, or otherbeneficial users. Specifically, a computer implemented method, accordingto various exemplary embodiments of the present invention can furtherinclude the steps of storing the unfiltered, unsorted seismic image datain a first database positioned to be in communication with the computer,storing the unfiltered wavefield constructed by the computer in thefirst computer process in a second database positioned to be incommunication with the computer, storing the filtered seismic image datagenerated by the computer in the eleventh computer process in a thirddatabase positioned to be in communication with the computer, andstoring the filtered seismic image generated by the computer in thetwelfth computer process in a fourth database positioned to be incommunication with the computer. Moreover, to further aid in theanalysis of filtered seismic images generated by methods according toexemplary embodiments of the present invention, such methods can furtherinclude the step of displaying the filtered seismic image generated bythe computer in the twelfth computer process on a display positioned tobe in communicated with the computer.

Exemplary embodiments of the present invention also beneficially includea computer implemented method to generate a filtered seismic data imageresponsive to seismic image data filtered through a single extrapolationby constructing a plurality of nonstationary convolution operators toperform localized filtering at each of a plurality of spatial locationsof a two-dimensional, unsorted, unfiltered pressure wavefield delineatedby unfiltered seismic image data. Spatial locations within thetwo-dimensional, unsorted, unfiltered pressure wavefield can bebeneficially defined by two coordinates, a first coordinate representinga spatial location within a transverse plane and a second coordinaterepresenting a spatial location within a depth plane. Stateddifferently, the two-dimensional, unsorted, unfiltered pressurewavefield can be defined as a two-dimensional plane where each pointwithin the plane is defined in terms of its transverse coordinate withinthe two-dimensional plane and its depth coordinate within thetwo-dimensional plane. Additionally, according to various exemplaryembodiments of the present invention, the depth dimension of thetwo-dimensional, unsorted, unfiltered pressure wavefield can be borderedat the highest depth by a recording surface plane and at the lowestdepth by a plane defining the lowest depth of a surface wave propagationzone, as is known and understood by those skilled in the art. Moreover,the two-dimensional, unsorted, unfiltered pressure wavefield can bebordered in the transverse dimension, for example, by two selectedtransverse boundaries.

Accordingly, such a computer implemented method according to anembodiment of the present invention can include, for example, theinitial steps of receiving from a seismic image receiver at a recordingsurface a plurality of seismic energy signals that have propagatedthroughout a two-dimensional surface wave propagation zone, as is knownand understood by those skilled in the art, and converting, by acomputer the plurality of seismic energy signals received from theseismic energy receiver into unfiltered, unsorted seismic image data,and constructing, by the computer based on the unfiltered, unsortedseismic image data, a two-dimensional, unsorted, unfiltered pressurewavefield including a plurality of spatial locations each defined by atransverse coordinate and a depth coordinate. Once the two-dimensional,unsorted, unfiltered pressure wavefield has been constructed, thecomputer implemented method can proceed to filter the two-dimensional,unsorted, unfiltered pressure wavefield. Accordingly, such a computerimplemented method according to various exemplary embodiments of thepresent invention can further include the step of locating, by thecomputer, a selected one of the plurality of spatial locations at apoint where the depth level coordinate of the selected one of theplurality of spatial locations is equal to a depth level coordinate ofthe recording surface and the transverse coordinate of the selected oneof the plurality of spatial locations is equal to a transversecoordinate of a first transverse boundary of the two-dimensional surfacewave propagation zone, as is known and understood by those skilled inthe art.

With a selected starting point now in place, i.e., the selected one ofthe plurality of spatial locations, such a computer implemented methodaccording to exemplary embodiments of the present invention can proceedto filter the two-dimensional, unsorted, unfiltered pressure wavefieldby repeating the following filtering steps for each location within thetwo-dimensional, unsorted, unfiltered pressure wavefield. The filteringsteps included in such a computer implemented method include, forexample, the steps of determining by the computer, for the selected oneof the plurality of spatial locations within the two-dimensional,unsorted, unfiltered pressure wavefield, a space-variant velocity basedon the transverse coordinate of the selected one of the plurality ofspatial locations, and determining by the computer responsive todetermining the space-variant velocity, for the selected one of theplurality of spatial locations within the two-dimensional, unsorted,unfiltered pressure wavefield, a quotient of a temporal frequency of theselected one of the plurality of spatial locations (indicated orrepresented by ω) and the space-variant velocity of the selected one ofthe plurality of spatial locations (indicated or represented by v(x)) tothereby define a mathematical function indicated or represented by k(x).Such filtering steps can also include, for example, the step ofdetermining by the computer responsive to determining k(x), for theselected one of the plurality of spatial locations within thetwo-dimensional, unsorted, unfiltered pressure wavefield, an exponentialfunction of a product of (i) a square root of negative one (indicated orrepresented by the imaginary number, i), (ii) a preselected wavefielddepth increment (indicated or represented by Δz), and (iii) a squareroot of (1) a square of a transverse wavenumber (indicated orrepresented by k_(x)) of the selected one of the plurality of spatiallocations subtracted from (2) a square of k(x) (√{square root over(k(x)²−k_(x) ²)}), to thereby define a multi-variable mathematicalfunction indicated or represented by Ŵ(k_(x), k(x), Δz).

Furthermore, the filtering steps included in such a computer implementedmethod according to an exemplary embodiment of the present invention canfurther include, for example, the step of determining by the computerresponsive to determining Ŵ(k_(x), k(x), Δz), for the selected one ofthe plurality of spatial locations within the two-dimensional, unsorted,unfiltered pressure wavefield, a product of (i) a quotient of one and aproduct of two and pi (indicated or represented by π)

$\left( \frac{1}{2\pi} \right)$

and (ii) an integral over a set of real numbers (indicated orrepresented by

), with respect to the transverse wavenumber of the selected one of theof the plurality of spatial locations (k_(x)), of a product of Ŵ(k_(x),k(x), Δz) and an exponential function of: (1) a product of negativesquare root of negative one (indicated or represented by the imaginarynumber, i), (2) the transverse wavenumber of the selected one of theplurality of spatial locations (k_(x)), and (3) a difference between thetransverse coordinate of the selected one of the plurality of spatiallocations (indicated or represented by x′) and a transverse coordinateof a second one of the plurality of spatial locations (indicated orrepresented by x) where the second one of the plurality of spatiallocations is located at a point closer to a second transverse boundaryof the two-dimensional surface wave propagation zone than the selectedone of the plurality of spatial locations

$\left( {\frac{1}{2\pi}{\int_{\Re}{{\hat{W}\left( {k_{x},{k(x)},{\Delta \; z}} \right)}^{{- }\; {k_{x}{({x - x^{\prime}})}}}{k_{x}}}}} \right),$

to thereby define a multi-variable mathematical function indicated orrepresented by W(x-x′, k(x), Δz). Once W(x-x′, k(x), Δz) is determined,the computer implemented method can further determine, for example, bythe computer responsive to determining W(x-x′, k(x), Δz), a complexconjugate of W(x-x′, k(x), Δz), to thereby define a multi-variablemathematical function indicated or represented by W*(x-x′, k(x), Δz). Acomplex conjugate, as is known and understood by those skilled in theart, can be defined as one or a pair of complex numbers, each having thesame real parts but with imaginary parts that differ in sign. Forexample, the numbers 2+3i and 2−3i are complex conjugates of each otheras is known and understood by those skilled in the art.

Such filtering steps of a computer implemented method according toexemplary embodiments of the present invention can further include thebeneficial step of building by the computer responsive to determiningW(x-x′, k(x), Δz) and determining W*(x-x′, k(x), Δz), a nonstationaryconvolution operator for the selected one of the plurality of spatiallocations within the two-dimensional, unsorted, unfiltered pressurewavefield by taking an integral over a set of real numbers (

), with respect to the transverse coordinate of the selected one of theplurality of spatial locations (x′), of a product of W(x-x′, k(x), Δz)and W*(x-x′, k(x), Δz)

(∫_(ℜ)W(x − x^(′), k(x), Δ z)W^(*)(x − x^(′), k(x), Δ z)x^(′)),

to thereby define a multi-variable mathematical function indicated orrepresented by P(x-x′, k(x), Δz). Moreover, such filtering steps canfurther beneficially include, by way of example, the step ofextrapolating, by the computer, the two-dimensional, unsorted,unfiltered pressure wavefield at the selected one of the plurality ofspatial locations within the two-dimensional, unsorted, unfilteredpressure wavefield using the nonstationary convolution operator for theselected one of the plurality of spatial locations built by the computerby taking an integral over a set of real numbers (

) of a product of P(x-x′, k(x) Δz) and the two-dimensional, unsorted,unfiltered pressure wavefield (indicated or represented by Ψ(x, z+Δz, ω)

(∫_(ℜ)ψ(x^(′), z, ω)P(x − xi, k(x), Δ z)x^(′)),

to thereby perform localized filtering of the selected one of theplurality of spatial locations (indicated or represented by amulti-variable mathematical function ψ(x, z+Δz, ω)). Each repetition ofthe aforementioned filtering steps can be, for example, described as asingle iteration of the filtering process.

A computer implemented method according to the present invention canfurther include, for example, the step of generating at each iteration,by the computer, filtered seismic image data responsive toextrapolating, by the computer, the two-dimensional unfiltered pressurewavefield at the selected one of the plurality of spatial locationswithin the two-dimensional unfiltered pressure wavefield. Additionally,the computer implemented method can beneficially include, for example,the step of generating, by the computer, a filtered seismic image basedon the filtered seismic image data generated at each iteration by thecomputer.

Various other embodiments of the present invention beneficially providea computer readable program product stored in a tangible computerreadable storage medium and including instructions that when executed bya computer cause the computer to perform the operations of constructingan unfiltered wavefield delineated by a plurality of spatial locationsfrom unfiltered, unsorted seismic image data based on a plurality ofseismic energy signals propagated through a surface wave propagationzone, as known and understood by those skilled in the art, received froma seismic image receiver, and building, for each of the plurality ofspatial locations of an unfiltered wavefield derived from theunfiltered, unsorted seismic image data, a plurality of nonstationaryconvolution operators, one for each of the plurality of spatiallocations of the unfiltered wavefield, each of the nonstationaryconvolution operators being based on the coordinate location of each ofthe plurality of spatial locations of the unfiltered wavefield and thespace-variant velocity, temporal frequency, transverse wavenumber, andwavelength of the unfiltered wavefield at each spatial location. Such anexemplary computer readable program product can also beneficiallyinclude, for example, instructions that when executed by the computercause the computer to perform the operations of filtering, in aspace-frequency domain, each of the plurality of spatial locations ofthe unfiltered wavefield using, at each of the plurality of spatiallocations, at least one of the plurality of nonstationary convolutionoperators built associated with that one of the plurality of spatiallocations and generating a filtered seismic image responsive to each ofthe plurality of spatial locations of the unfiltered wavefieldresponsive to filtering, in the space-frequency domain, each of theplurality of spatial locations of the unfiltered wavefield.

Various embodiments of the present invention can provide numerousbenefits, including but not limited to the following: (1) accuratelyfilter unfiltered seismic images based on seismic energy signalspropagated by a seismic energy source throughout a propagation zone andreceived by a seismic energy receiver; (2) nonstationary convolutionoperator filters can be implemented in the seismic energy source domainor the seismic energy receiver domain; (3) provide more computationallyefficient filtering processes for unfiltered seismic images; (4) filtera seismic image using only a single downward extrapolation without theneed to upward continue the seismic data back to the recording surfacedomain following filtration; (5) filter seismic energy data withouthaving to first sort such seismic energy data; (6) lower the cost ofsubsurface mineral deposit exploration by lowering the cost ofsubsurface seismic imaging; (7) increase the supply of oil into themarketplace by increasing the accuracy and efficiency of subsurfaceseismic imaging thereby lowering the cost of oil at the pump; and (8)increase the speed of subsurface seismic image filtration so thatfiltered seismic images can be viewed on a display in real time therebyallowing the such filtered seismic images to be quickly and efficientlyanalyzed by a subsurface seismic engineer without having to endure asubstantial delay due to lengthy, off-site seismic image filtration.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the features and benefits of variousembodiments of the invention, as well as others which will becomeapparent, can be understood in more detail, a more particulardescription of the various embodiments of the invention can be had byreference to the embodiments thereof which are illustrated in theappended drawings, which form a part of this specification. It is alsoto be noted, however, that the drawings illustrate only variousembodiments of the invention and are therefore not to be consideredlimiting of the invention's scope as it can include other effectiveembodiments as well.

FIG. 1 is high-level schematic block flow diagram of a system togenerate a filtered seismic image responsive to seismic image datafiltered by attenuating coherent seismic noise from unfiltered seismicimage data through a single downward extrapolation of the unfilteredseismic image data using a plurality of nonstationary convolutionoperators as local filters according to an exemplary embodiment of thepresent invention.

FIG. 2 is a schematic block diagram of a filtered seismic image createdand produced on one or more output devices adapted to be incommunication with a computer responsive to filtered seismic image datagenerated by attenuating coherent seismic noise from surface waves of anunfiltered wavefield constructed from the seismic image data using aplurality of nonstationary convolution operators according to anexemplary embodiment of the present invention.

FIG. 3 is a high-level schematic block flow diagram of a computerimplemented method to generate a filtered seismic image through a singledownward extrapolation using a plurality of nonstationary convolutionoperators as local filters according to an exemplary embodiment of thepresent invention.

FIG. 4 is a high-level schematic block flow diagram of a computerimplemented method to generate a filtered seismic image through a singleextrapolation by constructing a plurality of nonstationary convolutionoperators to perform localized filtering according to an exemplaryembodiment of the present invention.

FIG. 5 is a low-level, detailed schematic block flow diagram of acomputer implemented method to generate a filtered seismic data imagethrough a single downward extrapolation by constructing a plurality ofnonstationary convolution operators to perform localized filtering ateach of a plurality a spatial locations of a two-dimensional, unsorted,unfiltered pressure wavefield according to an exemplary embodiment ofthe present invention.

FIG. 6 is a high-level schematic block flow diagram illustrating themathematical inputs used by a nonstationary seismic data filter and theoutput of such a nonstationary seismic data filter according to anexemplary embodiment of the present invention.

FIG. 7 is a low-level, detailed schematic block mathematical flowdiagram illustrating various mathematical calculations and manipulationsof unfiltered seismic image data recursively performed by anonstationary seismic data filter in order to generate a filteredseismic data image through a single downward extrapolation of unfilteredseismic image data according to an exemplary embodiment of the presentinvention.

FIG. 8 is a low-level, detailed schematic block mathematical flowdiagram illustrating various mathematical calculations and manipulationsof unfiltered seismic image data performed in a doubly-recursive processby a nonstationary seismic data filter in order to generate a filteredseismic data image through a single downward extrapolation of unfilteredseismic image data according to an exemplary embodiment of the presentinvention.

FIG. 9 is a high-level schematic block flow diagram illustrating the useof a seismic image filtering machine to create a filtered seismic imageresponsive to filtered seismic image data generated by attenuatingcoherent seismic noise from surface waves of an unfiltered wavefieldconstructed from unfiltered seismic image data through a single downwardextrapolation of the unfiltered wavefield using a plurality ofnonstationary convolution operators to perform localized filtering ateach of a plurality of spatial locations of the unfiltered wavefieldaccording to an exemplary embodiment of the present invention.

FIG. 10 is a low-level, detailed schematic block flow diagram of aseismic image filtering machine to create a filtered seismic imageresponsive to filtered seismic image data generated by attenuatingcoherent seismic noise from surface waves of an unfiltered wavefieldconstructed from unfiltered seismic image data through a single downwardextrapolation of the unfiltered wavefield using a plurality ofnonstationary convolution operators to perform localized filtering ateach of a plurality of spatial locations of the unfiltered wavefieldaccording to an exemplary embodiment of the present invention.

FIG. 11 is a low-level schematic block flow diagram of a seismic imagefiltering system to generate a filtered seismic image based on seismicimage data filtered by attenuating coherent seismic noise from surfacewaves of an unfiltered wavefield constructed from the seismic image datathrough a single downward extrapolation using a plurality ofnonstationary convolution operators to perform localized filtering ateach of a plurality of spatial locations of the unfiltered wavefieldaccording to an exemplary embodiment of the present invention.

FIG. 12 is an unfiltered seismic image, specifically, a shot gather,produced using a synthetic dataset modeled over complex geology andrough topography according to an embodiment of the present invention.

FIG. 13 is a filtered seismic image, specifically, a shot gather,produced using a synthetic dataset modeled over complex geology andrough topography and filtered according to an embodiment of the presentinvention.

FIG. 14 is the difference between the results in FIG. 12 and FIG. 13calculated by subtracting the filtered seismic image of a syntheticdataset (FIG. 13) from the unfiltered seismic image of a syntheticdataset (FIG. 12) according to an embodiment of the present invention.

FIG. 15 is a near surface velocity model of a real dataset whererefraction tomography was used acquired from an irregular surface withnear surface lateral velocity variations according to an embodiment ofthe present invention.

FIG. 16 is an unfiltered seismic image, specifically, a shot gather,produced using a real dataset acquired from an irregular surface withnear surface velocity variations according to an embodiment of thepresent invention.

FIG. 17 is a filtered seismic image, specifically, a shot gather,produced using a real dataset acquired from an irregular surface withnear surface velocity variations and filtered according to an embodimentof the present invention.

FIG. 18 is the difference between the results in FIG. 16 and FIG. 17calculated by subtracting the filtered shot gather of a real dataset(FIG. 17) from the unfiltered shot gather of a real dataset (FIG. 16)according to an embodiment of the present invention.

FIG. 19 is an enlarged view of an unfiltered seismic image,specifically, a seismic stack result, produced using a real datasetacquired from a complex, shallow geological formation according to anembodiment of the present invention.

FIG. 20 is an enlarged view of an filtered seismic image, specifically,a seismic stack result, produced using a real dataset acquired from acomplex, shallow geological formation and filtered according to anembodiment of the present invention.

FIG. 21 is an enlarged view of an unfiltered seismic image,specifically, a seismic stack result, produced using a real datasetacquired from a complex, deep geological formation according to anembodiment of the present invention.

FIG. 22 is an enlarged view of a filtered seismic image, specifically, aseismic stack result, produced using a real dataset acquired from acomplex, deep geological formation and filtered according to anembodiment of the present invention.

DETAILED DESCRIPTION

The present invention will now be described more fully hereinafter withreference to the accompanying drawings which illustrate variousembodiments of the invention. This invention, however, may be embodiedin many different forms and should not be construed as limited to theembodiments set forth herein. Rather, these embodiments are provided sothat this disclosure will be thorough and complete, and will fullyconvey the scope of the invention to those skilled in the art. It is tobe fully recognized that the different teachings of the variousembodiments discussed below may be employed separately or in anysuitable combination to produce desired results. The variouscharacteristics mentioned above, as well as other features andcharacteristics described in more detail below, will be readily apparentto those skilled in the art upon reading the following detaileddescription of the various embodiments, and by referring to theaccompanying drawings. In the drawings and description that follows,like parts are marked throughout the specification and drawings with thesame reference numerals, respectively. The prime notation, if used,indicates similar elements in alternative embodiments. The drawings arenot necessarily to scale. Certain features of the disclosure may beshown exaggerated in scale or in somewhat schematic form and somedetails of conventional elements may not be shown in the interest ofclarity and conciseness.

In the drawings and description that follows, like parts are markedthroughout the specification and drawings with the same referencenumerals, respectively. The drawings are not necessarily to scale.Certain features of the disclosure can be shown exaggerated in scale orin somewhat schematic form and some details of conventional elements cannot be shown in the interest of clarity and conciseness. The presentdisclosure is susceptible to embodiments of different forms. Specificembodiments are described in detail and are shown in the drawings, withthe understanding that the present disclosure is to be considered anexemplification of the principles of the disclosure, and is not intendedto limit the disclosure to that illustrated and described herein. It isto be fully recognized that the different teachings of the embodimentsdiscussed below can be employed separately or in any suitablecombination to produce desired results. The various characteristicsmentioned above, as well as other features and characteristics describedin more detail below, will be readily apparent to those skilled in theart upon reading the following detailed description of the embodiments,and by referring to the accompanying drawings.

Embodiments of the present invention advantageously provide, forexample, systems, machines, computer readable program products, andassociated computer implemented methods to attenuate coherent seismicnoise from surface waves using nonstationary filters that require only asingle extrapolation process, which can be implemented either in thesource or receiver domain, and do not require sorting operations. Thisapproach, for example, can handle strong lateral velocity variationsmaking it an effective tool to remove complicated coherent seismic noisewhich is typically in the form of exponentially decaying evanescentwaves. These embodiments, for example, use specially designedmathematical operators that are implemented in the two-dimensionalspace-frequency domain as nonstationary filters.

More particularly, embodiments of the present invention advantageouslyprovide, for example, seismic image filtering machines, systems,computer implemented methods, and computer readable program products togenerate a filtered seismic image based on seismic image data filteredby attenuating coherent seismic noise from surface waves of anunfiltered wavefield—which is constructed from unfiltered seismic imagedata gathered from seismic energy detectors, receivers or sensors—usinga plurality of nonstationary convolution operators as local filters thatrequire only a single extrapolation process, which can be implementedeither in the source or receiver domain, and which do not require anysorting operations. Various embodiments of the invention, for example,can beneficially handle strong lateral velocity variations thus makingvarious embodiments of the present invention effective tools to removecomplicated coherent seismic noise which is typically in the form ofexponentially decaying evanescent waves. Embodiments of the presentinvention, for example, use, as a part of the filtering mechanism,specially designed nonstationary convolution operators that areimplemented in the space-frequency domain as nonstationary filters.According to various embodiments of the present invention, suchnonstationary convolution operators are constructed at each of theplurality of spatial locations of an unsorted wavefield so that each ofthe plurality of spatial locations of the unsorted wavefield can belocally filtered in a single extrapolation process.

As is perhaps best illustrated by FIG. 1, various embodiments of thepresent invention can include, by way of example, a system to generate afiltered seismic image responsive to filtered seismic image dataproduced by attenuating coherent seismic noise from surface wavesthrough a single downward extrapolation of unfiltered seismic image datausing a plurality of nonstationary convolution operators as localfilters. More particularly, FIG. 1 illustrates a high-level, schematic,block flow diagram overview of such an exemplary system to generate afiltered seismic image responsive to filtered seismic image dataproduced by attenuating coherent seismic noise from surface waves usingnonstationary seismic image data filters. Such a system can include, forexample, a seismic energy source 10, a seismic energy receiver 20, anunfiltered seismic image 30 such as, a shot gather or a seismic stackproduced by a computer responsive to seismic energy signals received bythe seismic energy receiver, a nonstationary seismic image data filter40 that includes a nonstationary convolution operator 50, a filteredseismic image 60 generated by the computer responsive to seismic energydata filtered by the nonstationary seismic image data filter, and one ormore output devices 70. According to various embodiments of the presentinvention, the seismic energy source 10 can include any seismic oracoustic energy whether from an explosive, implosive, swept-frequency orrandom sources. The seismic energy source, for example, can generate aseismic energy signal that propagates into the earth 80. As illustratedin FIG. 1, the earth 80 can, for example, take the form of complexgeology or topography.

Generally, a seismic energy source 10 can emit seismic waves into theearth 80 to evaluate subsurface conditions and to detect possibleconcentrations of oil, gas, and other subsurface minerals.Mathematically, seismic waves are waves of force that travel through anelastic body (such as the earth 80) as the result of a natural phenomena(such as an earthquake), a man-made energy (such as an explosion), orsome other process that imparts forces into the elastic body (i.e., theearth 80). Seismic energy waves, for example, can occur naturally as theresult of the pounding of ocean waves onto the shore. The propagationvelocity of seismic waves can depends on the particular elastic mediumthrough which the waves travel, particularly the density and elasticityof the medium as is known and understood by those skilled in the art.For instance, the propagation velocity of seismic waves can range fromapproximately three to eight (3-8) kilometers per second (km/s) in theearth's 80 crust to up to thirteen (13) kilometers per second (km/s) inthe earth's 80 deep mantle. Generally, in the field of geophysics, as isknown and understood by those skilled in the art, the refraction orreflection of seismic waves onto a seismic energy receiver 20 can beused to research and investigate subsurface structures of the earth 80.

Accordingly, seismic energy receivers 20 can be positioned to receiveand record seismic energy data or seismic field records in any formincluding, but not limited to, a geophysical time series recording ofthe acoustic reflection and refraction of waveforms that travel from theseismic energy source 10 to the seismic energy receiver 20. Variationsin the travel times of reflection and refraction events in one or morefield records in seismic data processing can produce a seismic image 30,defined by unfiltered seismic image data 35, that demonstratessubsurface structure according to an exemplary embodiment of the presentinvention. Beneficially, such a seismic image 30 can be used to aid inthe search for, and exploitation of, subsurface mineral deposits;however, in order for the seismic image to be of the greatestfunctionality, it must first be filtered.

Generally speaking, seismic image receiver devices 20 can record soundwave echoes (otherwise known as seismic energy signal reflections) thatcome back up through the ground from a seismic energy source 10 to arecording surface. Such seismic image receiver devices 20 can record theintensity of such sound waves and the time it took for the sound wave totravel from the sound source (or seismic energy source) device 10 backto the seismic energy receiver device 20 at the recording surface.According to various exemplary embodiments of the present invention, forexample, during the seismic imaging process, the reflections of soundwaves emitted by a seismic energy source device 10, and recorded by aseismic energy recording device 20, can be processed by a computer togenerate a three-dimensional digital model, or seismic image, of thesubsurface. The three-dimensional model of the subsurface can be used toidentify, for example, the placement of wells and potential well flowpaths.

More specifically, the term seismic energy receiver 20 as is known andunderstood by those skilled in the art, can include geophones,hydrophones and other sensors designed to receive and record seismicenergy. A geophone, generally speaking, is a seismic energy receiverdevice 20 which converts ground movement (or displacement of the ground)into voltage which may be recorded at a recording station. A deviationof the measured voltage from a base line measured voltage produces aseismic response which can be analyzed and processed by a computer toproduce an unfiltered seismic image of subsurface geophysicalstructures. Although seismic energy waves propagating through the earth80 are three-dimensional by nature, geophones are generally constrainedto respond to a single dimension—typically the vertical dimension. Thus,geophones are often used in reflection seismology to record seismicenergy waves reflected by the subsurface geology. Accordingly, byplacing a plurality of geophone seismic energy receivers 20 at arecording surface, a two-dimensional seismic image can be producedresponsive to voltage difference data collected by the geophone seismicenergy receivers 20. Hydrophones, as are known and understood by thoseskilled in the art, are another type of seismic energy receiver device20 designed specifically for underwater recording or listening tounderwater sound. Most hydrophones are based on a piezoelectrictransducer, as is known and understood by those skilled in the art, thatgenerates electricity when subjected to a pressure change. Piezoelectrictransducers can, accordingly, covert a seismic energy signal into anelectric signal since seismic energy signals are a pressure wave influids.

According to an exemplary embodiment of the present invention, a seismicenergy receiver 20 can be positioned to receive and record seismicenergy data or seismic field records in any form including a geophysicaltime series recording of the acoustic reflection and refraction ofwaveforms that travel from the seismic energy source 10 to the seismicenergy receiver 20. Variations in the travel times of reflection andrefraction events in one or more field records in a plurality of seismicsignals can, when processed by a computer, produce a seismic image 30,defined by unfiltered seismic image data 35, that demonstratessubsurface structure. Such a seismic image 30, however, is unfilteredand accordingly, it may, in many instances, contain not only seismicimage data but also complicated coherent seismic noise in the form ofevanescent waves as known and understood by those skilled in the art.Such complicated coherent seismic noise with respect to an unfilteredseismic image 30 is similar to fuzz or grain on a image taken with afilm camera. By applying certain filters to the film image, it ispossible, in many instances, to remove such fuzz or grain. The same istrue for complicated coherent seismic noise present in an unfilteredseismic image 30. Accordingly, prior to using a seismic image 30 to aidin the search for, and exploitation of, mineral deposits, the seismicimage 30 should first be filtered according to an exemplary embodimentof the present invention.

Although a seismic image 30 can be useful for delineating features inthe earth's surface and subsurface, the seismic image 30 often depictsundesired dispersive energy, such as coherent seismic noise, in additionto desired energy. Portions of the unwanted energy can overwhelm,interfere with, or otherwise mask portions of the seismic image usefulfor delineating features in the earth's surface. Particularly, whenpropagating through an irregular near surface, such as rugged topographyor complex geology 80, seismic energy signals can have complicated wavepaths and lateral velocity variations thereby resulting in unwanteddispersive energy. Much of this energy propagates horizontally in thenear surface. In the presence of complex geology and rugged topography,the energy can have a complicated wave path, thus making its removal achallenging task. Nevertheless, removing this dispersive energy is animportant step to focus the seismic image 30 so that, for example, theimage is useful for extracting seismic attributes, for analyzing seismicwaveform velocity, and for wavelet processing.

More particularly, as is known and understood by those skilled in theart, there are two types of seismic waves, surface waves and body waves.Generally speaking, body waves travel through the interior of the Earthwhile surface waves travel just under the Earth's surface. Surfacewaves, as is known and understood by those skilled in the art, can becompared analogously to water waves and travel more slowly than bodywaves. In the field of physics, a surface wave is typically described bythose skilled in the art as a type of mechanical wave that propagatesalong the interface between differing media, such as two fluids withdifferent densities, or the earth's 80 crust and the earth's more denseupper mantle. Due to the complex and often rugged topography of theearth's 80 surface, surface waves can often have complicated wave pathswhen propagating through the earth's 80 surface. Such surface waves,when received and recorded by a seismic energy receiver 20 can result incoherent seismic noise that can make reading and analyzing a seismicimage of subsurface structures difficult.

According to an exemplary embodiment of the present invention, anonstationary seismic image data filter 40 can be implemented in thespace-frequency domain and can include a nonstationary convolutionoperator 50 designed using a weighted least squares with a transitionband approach, as is known and understood by those skilled in the art.Conceptionally, convolution, as is known and understood by those skilledin the art, can be described as the process of replacing each point ofdata of an unfiltered image by a scaled copy of a convolution filter oroperator. Commonly, convolution operators (or filters), as is known andunderstood in the art, are stationary, meaning that the operator's formdoes not change with space or time. While such stationary convolutionoperators accurately filter more traditional images, a stationaryconvolution operator's inability to change its form with space or time(i.e., velocity) is often too limiting to accurately filter geophysicalseismic images.

According to various exemplary embodiments of the present invention,unfiltered seismic image data 35 can be used to construct, by acomputer, an unfiltered wavefield including a plurality of wavelets anddelineated by a plurality of spatial locations as is known andunderstood by those skilled in the art. The velocity of various spatiallocations within such an unfiltered wavefield can vary from spatiallocation to spatial location and as such, stationary convolutionoperators are unable to provide the needed flexibility. A mathematicalprocess which can form a scaled superposition of a filter while allowingthe wavelet radius to depend on a local velocity at a spatial locationof within a wavefield is known and understood by those skilled in theart as a nonstationary convolution. Beneficially, and unlike stationaryconvolution operators, nonstationary convolution operators 50, accordingto various exemplary embodiments of the present invention, can changeform, for example, in a controlled fashion with time and space. That is,nonstationary convolution operators 50 can beneficially be, for example,dependent on velocity measurements at various spatial locations of anunfiltered wavefield formed from unfiltered seismic image 30 defined bya plurality of unfiltered seismic image data 35 according to variousexemplary embodiments of the present invention. Thus, such nonstationaryconvolution operators can, for example, be used to filter an unfilteredseismic image 30 to thereby generate a filtered seismic image 60.

Such a nonstationary seismic image data filter 40, according to anexemplary embodiment of the present invention, can be configured, forexample, to attenuate coherent seismic energy, or noise, from theseismic image 30. The nonstationary seismic image data, according to anexemplary embodiment of the present invention, can apply a nonstationaryconvolution operator to downwardly continue the plurality of unfilteredseismic image data 35 that defines the seismic image 30 to a depth levelbelow the surface wave propagation zone to thereby generate new filteredseismic image data 65 that define a filtered seismic image 60.

Beneficially, and as described in greater detail herein, thenonstationary seismic image data filter 40 can filter the unfilteredseismic image 30, for example, through only a single downwardextrapolation process and without the need to sort the unfilteredseismic image data 35. When compared to other filter configurationswhich require multiple data extrapolation processes and a sorted dataset, the embodied filter enhances the speed and efficiency of currentseismic filters by reducing the process steps necessary to filter aseismic image. Generally, images of various types, including bothfiltered 60 and unfiltered 30 seismic images, can be represented by aplurality of image data points typically in the form of an image matrixas is known and understood by those skilled in the art. As is perhapsbest illustrated in FIG. 2, such an image matrix can be processed andmanipulated by a computer in order to produce a human-readable versionof the image represented by the plurality of image data points on one ormore output devices 70 adapted to be in communication with the computer90.

The one or more output devices adapted to be in communication with thecomputer 90 can be in communication with the computer through acommunications network 95 as is known and understood by those skilled inthe art. The communications network 95 can include, for example, a localarea network, a wide area network, a telephony network, a wirelinenetwork, a wireless network, a wide area network, an infrared network, aradio-frequency network, an optical network, or any other communicationsnetwork now or hereinafter created as is known and understood by thoseskilled in the art. Seismic energy source devices 10 and seismic energyreceiver devices 20 can, according to exemplary embodiments of thepresent invention, be adapted to be in communication with a computer 90via a communications network 95. Furthermore, seismic energy sourcedevices 10 and seismic energy receiver devices 20 can alternatively bepositioned, for example, to be in communication with a computer 90without the need for a communications network 95. Seismic image data caninclude, for example, a plurality of image data points, as is known andunderstood by those skilled in the art. Furthermore, the plurality ofseismic image data points can be in the form of an array, a linked-list,a matrix, a queue, a stack, a tree, a binary tree, a b-tree, a hashtable, a heap, a binomial heap, a set, a disjoint set, or any other datastructure now or hereinafter developed as is known or understood bythose skilled in the art.

Accordingly, various exemplary embodiments of the present invention canbeneficially produce, for example, a filtered seismic image 65 on anoutput device 70 adapted to be in communication with a computer 90responsive to seismic image data filtered by attenuating coherentseismic noise from an unfiltered seismic image data using a plurality ofnonstationary convolution operators as local filters. Filtered seismicimage data, according to various embodiments of the present invention,for example, can be converted, by a computer 90, from a matrix of datapoints 60 (as further described above) into a graphic image (or othergraphic image form) 65 capable of being displayed on a display 70,printed to a printer 70′, or otherwise produced via an output device. Anoutput device 70 can include, for example, a printer, a brail printer, atelevision, a monitor, a CRT monitor, an LCD monitor, a plasma monitor,an OLED screen, a DLP monitor, a video projection, a three-dimensionalprojection, a touch screen, and any other piece of electronic hardwareequipment used to communicate the results of data processing carried outby any information processing system (such as a computer) now orhereinafter developed as is known or understood by those skilled in theart. Moreover, as used throughout, the term display can include, forexample, a CRT monitor, a LCD monitor, a plasma monitor, a OLED screen,a television, a DLP monitor, a video projection, a three-dimensionalprojection, a touch screen, and any other graphical user interfacedevice currently or hereinafter developed as is known and understood bythose skilled in the art.

Consider, for instance, that a typical sorting routine can requireoperations on the order of n-squared, where n is the number of datapoints to be sorted. For example, up to ten-thousand (10,000) processsteps could be required to sort seismic image data containingone-hundred (100) seismic image data points. A nonstationary seismicimage filter according to various embodiments of the present inventiontherefore can improve the speed and efficiency of the rate at whichseismic images are filtered by eliminating the onerous requirement ofsorted data. Additionally, the embodied filter enhances the speed andefficiency of the filtering process by using only a single downwardextrapolation process where current filters require both a downwardextrapolation of the unfiltered seismic energy data throughout a definedpropagation zone of the seismic energy surface wave signals followed byan upward continuation of the unfiltered seismic energy data back up toa recording surface of the seismic energy signals.

Beneficially, for example, the nonstationary seismic image data filter60 can handle strong lateral velocity variation thereby making it aneffective tool to remove complicated coherent noise due to complexgeology or rugged topography 80. Generally, the nonstationary seismicimage data filter 60 can be beneficially derived from thespace-frequency explicit wavefield extrapolation imaging algorithm sothat nonstationary seismic image data filters 60 according to variousembodiments of the present invention can be beneficially implemented inlegacy systems and with legacy software. At each lateral spatiallocation, the velocity information of the seismic energy signal can beused to build nonstationary convolution operators which performlocalized filtering in the space-frequency domain. Furthermore, theconfiguration of the nonstationary convolution operators according toexemplary embodiments of the present invention can, for example, use thesame velocity model used for resolving near surface distortions.

FIGS. 3 through 8 illustrate, by way of example, various exemplarycomputer implemented methods according to embodiments of the presentinvention to generate a filtered seismic data image responsive toseismic image data filtered by attenuating coherent seismic noise fromsurface waves of an unfiltered wavefield constructed from unfilteredseismic image data through a single downward extrapolation usingspecially-constructed nonstationary convolution operators to performlocalized filtering at each of a plurality of spatial locations of anunfiltered wavefield defined by the unfiltered seismic image data. FIG.3 perhaps best illustrates a simplified form of such various computerimplemented methods to generate a filtered seismic data image responsiveto seismic image data filtered according to various exemplaryembodiments of the present invention. For example, such computerimplemented methods can include the steps of generating a plurality ofseismic energy signals using a seismic energy source that propagatesinto the earth and is at least partially reflected by subsurface seismicreflectors as is known and understood in the art (block 100), receivingand recording a plurality of reflections and refractions of theplurality of seismic energy signals using a seismic image receiver orsensor as is known and understood by those skilled in the art (block105), and converting the plurality of reflections and refractions of theplurality of seismic energy signals into unfiltered, unsorted seismicimage data as is known and understood by those skilled in the art (block110). The subsurface seismic reflectors that at least partially reflectthe plurality of seismic energy signals can include, for example,interfaces between underground formations having different acousticimpedances. The plurality of reflections and refractions of theplurality of seismic energy signals can be recorded (block 105), forexample, in one or more geophysical time series by seismic energyreceivers or sensors located at or near the surface of the earth, in abody of water, or at known depths in boreholes.

Once unfiltered, unsorted seismic image data is obtained from seismicenergy receivers, such computer implemented methods according to variousembodiments of the present invention can further include various stepsto filter the unfiltered, unsorted seismic image data to therebybeneficially generate a filtered seismic image. In particular, acomputer implemented method according to an exemplary embodiment of thepresent invention can further include the steps of transmittingunfiltered seismic image data to a nonstationary seismic image datafiltered (block 115), and filtering the unfiltered seismic image data(block 120) to thereby generate filtered seismic image data (block 125)by applying a nonstationary convolution operator to downwardly continuethe seismic data to a depth level below a propagation zone of theplurality of the seismic energy signals. The nonstationary seismic imagedata filter can, for example, be implemented in the space-frequencydomain, and the nonstationary convolution operator can, for example, bedesigned using a weighted least-squares with a transition band approach.Furthermore, according to an embodiment of the present invention, thepropagation zone of the plurality of seismic energy signals, as is knownand understood by those skilled in the art, can be defined to be thearea bounded at the top and at the bottom by the highest and lowestelevations, respectively, at which the plurality of seismic energysignals first propagate into the earth.

Furthermore, according to an exemplary embodiment of the presentinvention, such a computer implemented method can further include thesteps of generating a filtered seismic image (block 130) based on thefiltered seismic image data generated responsive to the step offiltering the unfiltered seismic image data (block 120), and displayingthe filtered seismic on a display. Additionally, according to anexemplary embodiment of the present invention, the step of filteringunfiltered seismic image data (block 120) to thereby beneficiallygenerate filtered seismic image data (block 125) by applying anonstationary convolution operator to downwardly continue the unfilteredseismic data to a depth level below a propagation zone of a plurality ofsurface waves produced by the plurality of the seismic energy signalscan further include the step of receiving as input, a temporal frequencybased on the unfiltered seismic image data as is known and understood bythose skilled in the art, a transverse wavenumber based on the pluralityof unfiltered seismic image data as is known and understood by thoseskilled in the art, a space-variant velocity field based on theplurality of unfiltered seismic image data as is known and understood bythose skilled in the art, the unfiltered seismic image data, ameasurement of the depth of a two-dimensional wavefield represented bythe unfiltered seismic image data as is known and understood by thoseskilled in the art, a depth iteration increment as is known andunderstood by those skilled in the art, a transverse coordinate of thetwo-dimensional wavefield at input as is known and understood by thoseskilled in the art, and a transverse coordinate of the two-dimensionalwavefield at output as is known and understood by those skilled in theart.

As is perhaps best illustrated by FIG. 4, other various embodiments ofthe present invention can provide a computer implemented method togenerate a filtered seismic data image based on filtered seismic imagedata generated by attenuating coherent seismic noise from surface wavesof an unfiltered wavefield, constructed from unfiltered seismic imagedata, through a single downward extrapolation usingspecially-constructed nonstationary convolution operators to performlocalized filtering at each of a plurality of spatial locations of theunfiltered wavefield. Such an exemplary computer implemented method caninclude, for example, the steps of receiving from a seismic imagereceiver, at a recording surface, a plurality of seismic energy signalsthat have propagated throughout a surface wave propagation zone (block150), converting the plurality of seismic energy signals received fromthe seismic energy receiver into unfiltered, unsorted seismic image data(block 155), and constructing an unfiltered wavefield delineated by aplurality of spatial locations from the unfiltered, unsorted seismicimage data based on the plurality of seismic energy signals that havepropagated through the surface wave propagation zone and have beenreceived and recorded by a seismic image receiver (block 160).Furthermore, such a computer implemented method according to variousexemplary embodiments of the present invention can further include thestep of building a plurality of nonstationary convolution operators, onefor each of the plurality of spatial locations of the unfilteredwavefield, responsive to constructing the unfiltered wavefield for eachof the plurality of spatial locations of the unfiltered wavefield (block165), and extrapolating, responsive to building each of the plurality ofnonstationary convolution operators, the unfiltered wavefield at each ofthe plurality of spatial locations of the unfiltered wavefield to adepth level below the surface wave propagation zone of the seismicenergy signals using, at each of the plurality of spatial locations, atleast one of the plurality of nonstationary convolution operators builtby the computer associated with that one of the plurality of spatiallocations, to thereby locally filter each of the plurality of spatiallocations of the unfiltered wavefield (block 170).

Each of the nonstationary convolution operators, for example, canbeneficially be based on the coordinate location of each of theplurality of spatial locations of the unfiltered wavefield within theunfiltered wavefield as is known and understood by those skilled in theart, and a space-variant velocity, temporal frequency, transversewavenumber, and wavelength of the unfiltered wavefield at each spatiallocation as are known and understood by those skilled in the art.Beneficially, such computer implemented methods according to variousexemplary embodiments of the present invention can further include thestep of stabilizing each of the nonstationary convolution operatorsbuilt by the computer for each of the plurality of spatial locations ofthe unfiltered wavefield (block 165) using a weighted least squares witha transition band approach as is known and understood by those skilledin the art and as is explained in greater detail herein. Furthermore,exemplary computer implemented methods according to various embodimentsof the present invention can further include the steps of generating afiltered seismic image responsive to each of the plurality of spatiallocations of the unfiltered wavefield locally filtered by the computer(block 175), and displaying the filtered seismic image generated by thecomputer on a display positioned to be in communicated with the computer(block 180).

According to exemplary embodiments of the present invention, each of theplurality of nonstationary convolution operators can be different fromeach of the others of the plurality of nonstationary convolutionoperators, and each of the plurality of nonstationary convolutionoperators can, for example, be uniquely associated with one of theplurality of spatial locations of the unfiltered wavefield so thatparticularized localized filtering can be beneficially performed at eachof the plurality of spatial locations of the unfiltered wavefield.Moreover, each of the plurality of nonstationary convolution operators,one for each of the plurality of spatial locations of the unfilteredwavefield, can be built, by way of example, by performing an inverseFourier transformation over the transverse wavenumber coordinate of apower of a phase shift operator at each of the plurality of spatiallocations of the unfiltered wavefield. Additionally, the step ofextrapolating responsive to building each of the plurality ofnonstationary convolution operators (block 170) can be implemented, forexample, in one of, of both, the seismic energy source domain or theseismic energy receiver domain.

Also according to an exemplary embodiment of the present invention, thestep of extrapolating the unfiltered wavefield at each of the pluralityof spatial locations of the unfiltered wavefield to a depth level belowthe surface wave propagation zone of the seismic energy signals tothereby locally filter each of the plurality of spatial locations of theunfiltered wavefield (block 170) can further include the step of takingan integral over a set of real numbers of a product of a nonstationaryconvolution operator built according to an exemplary embodiment of thepresent invention (indicated or represented by P(x-x′, k(x), Δz)) andthe unfiltered wavefield to thereby perform localized filtering of theselected one of the plurality of spatial locations. Furthermore, thestep of constructing the unfiltered pressure wavefield (block 160) canfurther include the step of constructing the unfiltered pressurewavefield further includes the step of performing a Fouriertransformation of the unfiltered wavefield over a temporal coordinate.Such exemplary computer implemented methods according to variousembodiments of the present invention can also include the step ofgenerating filtered seismic image data for each of the plurality ofspatial locations of the unfiltered wavefield responsive toextrapolating the unfiltered wavefield at each of the plurality ofspatial locations of the unfiltered wavefield, and the filtered seismicimage generated by the computer in the fourth computer process can bebased, for example, on the filtered seismic image data.

Moreover, a computer implemented method according to exemplaryembodiments of the present invention can further include the beneficialsteps of storing the unfiltered, unsorted seismic image data in a firstdatabase positioned to be in communication with the computer, storingthe unfiltered wavefield constructed by the computer in the firstcomputer process in a second database positioned to be in communicationwith the computer, storing the filtered seismic image data generated bythe computer in the eleventh computer process in a third databasepositioned to be in communication with the computer, and storing thefiltered seismic image generated by the computer in the twelfth computerprocess in a fourth database positioned to be in communication with thecomputer.

As is perhaps best illustrated by FIG. 5, various embodiments of thepresent invention can also provide a computer implemented method tofilter unfiltered, unsorted seismic image data through a singleextrapolation of the unfiltered, unsorted seismic image data byconstructing a plurality of nonstationary convolution operators toperform localized filtering at each of a plurality of spatial locationsof a two-dimensional, unsorted, unfiltered pressure wavefieldconstructed from the unfiltered, unsorted seismic image data. Such acomputer implemented method can include, for example, the steps ofreceiving from a seismic image receiver at a recording surface aplurality of seismic energy signals that have propagated throughout asurface wave propagation zone (block 200), converting the plurality ofseismic energy signals received from the seismic energy receiver intounfiltered, unsorted seismic image data (block 205), constructing, basedon the unfiltered, unsorted seismic image data, an unfiltered wavefieldincluding a plurality of spatial locations each defined by a transversecoordinate and a depth coordinate (block 210), and selecting as a firstspatial location within the unfiltered wavefield a location with atransverse coordinate at a first transverse boundary of the unfilteredwavefield and a depth coordinate of the location of the recordingsurface (block 215). The unfiltered wavefield, according to anembodiment of the present invention, can be, for example, atwo-dimensional, unsorted, unfiltered pressure wavefield.

A computer implemented method according to various embodiments of thepresent invention can also include the step of selecting as a nextspatial location within the unfiltered wavefield a location with atransverse coordinate closer to a second transverse boundary of theunfiltered wavefield than the first spatial location and a depthcoordinate at a current depth level (block 220). With the two referencelocations (i.e., the first spatial location and the next spatiallocation) selected, the computer implemented method according to anexemplary embodiment of the present invention can further include thesteps of building, for the first spatial location, a nonstationaryconvolution operator based on the coordinate location of the firstspatial location of the unfiltered wavefield and the space-variantvelocity, temporal frequency, transverse wavenumber, and wavelength ofthe unfiltered wavefield at the first spatial location (block 225).Following the step of building the nonstationary convolution operator(block 225), such a computer implemented method can further include thestep of filtering, in a space-frequency domain, the first spatiallocations of the unfiltered wavefield using the nonstationaryconvolution operator built for the first spatial location (block 230).Beneficially, such a computer implemented method can then furtherinclude the step of setting the transverse coordinate of the firstspatial location equal to the transverse coordinate of the next spatiallocation and repeating the steps outlined in blocks 220 to 235 until thenext special location is located at, or outside of, the secondtransverse boundary. Such a computer implemented method can subsequentlyinclude the step of increasing the current depth level by a preselecteddepth level increment and repeating the steps outlined in blocks 220 to240 until the current depth level is at, or below, the surface wavepropagation zone. After completing the recursive process outlined above,a computer implemented method according to an exemplary embodiment ofthe present invention can further include the steps of generating afiltered seismic image based on filtered seismic image data generatedresponsive to each of the plurality of spatial locations of theunfiltered wavefield filtered in the space-frequency domain (block 245),and lastly, displaying the filtered seismic image on a display deviceadapted to be in communication with the computer (block 250).

As is perhaps best illustrated in FIG. 6, a nonstationary seismic imagedata filter 40 according to various exemplary embodiments of the presentinvention can receive, for example, as input at each iteration of theprocess outlined above unfiltered seismic image data (indicated orrepresented by ψ) 35, a temporal frequency of an unfiltered wavefield(indicated or represented by ω) constructed from the unfiltered seismicimage data at a selected spatial location within the unfilteredwavefield as is known and understood by those skilled in the art 300, atransverse wavenumber (indicated or represented by k_(x)) of theunfiltered wavefield at the selected spatial location within theunfiltered wavefield as is known and understood by those skilled in theart 305, a space-variant velocity field (indicated or represented byv(x)) of the unfiltered wavefield at the selected spatial location withthe unfiltered wavefield as is known and understood by those skilled inthe art 310, a measurement of the depth of the unfiltered wavefield(indicated or represented by z) as is known and understood by thoseskilled in the art 320, a preselected depth iteration increment(indicated or represented by Δz) as is known and understood by thoseskilled in the art 325, a transverse coordinate at input (indicated orrepresented by x′) representing the transverse coordinate of the spatiallocation within the unfiltered wavefield currently being filtered 330,and a transverse coordinate at output (indicated or represented by x)representing the transverse coordinate of a next spatial location withinthe unfiltered wavefield to be filtered 335. Furthermore, thenonstationary seismic image data filter can provide, for example, asoutput, filtered seismic image data (indicated or represented by ψ) 65and a transverse coordinate at output (indicated or represented by x)representing the transverse coordinate of the next spatial locationwithin the unfiltered wavefield to be filtered by the nonstationaryseismic image data filter 65.

According to an exemplary embodiment of the present invention, thenonstationary convolution operator 50 can be implemented as a functionof multiple variables, the output of which can be, for example, seismicimage data resulting from the linear combination of output of aconvolution operator and output of the complex conjugate of the sameconvolution operator. Generally, convolution is a mathematical operationthat provides a way of multiplying together two arrays (or matrices) ofnumbers, generally of different sizes but of the same dimensionality, toproduce a third array (or matrix) of numbers of the same dimensionality.This can be used in image processing to implant operators whose outputpixel values are simple linear combinations of certain input pixelvalues.

More specifically, according to an embodiment of the present invention,as is perhaps best illustrated in FIG. 7, the 2D space-frequencyexplicit wavefield extrapolation algorithm, for example, can be used toextrapolate an unfiltered wavefield to a depth level below thepropagation zone of the coherent seismic noise according to amulti-variable mathematical function indicated or represented by

$\begin{matrix}{{{\psi \left( {x,{z + {\Delta \; z}},\omega} \right)} = {\int_{\Re}{{\psi \left( {x^{\prime},z,\omega} \right)}{W\left( {{x - x^{\prime}},{k(x)},{\Delta \; z}} \right)}{x^{\prime}}}}},} & \left( {{equation}\mspace{14mu} 1} \right)\end{matrix}$

where the mathematical symbol

refers to real numbers and k(x)=ω/v(x) (equation 2). Here, themathematical symbol ψ can represent, for example, a two-dimensional,unsorted, unfiltered pressure wavefield 35 after a Fouriertransformation of the two-dimensional, unsorted, unfiltered pressurewavefield 35 has been performed over the temporal coordinate.Furthermore, according to exemplary embodiments of the presentinvention, the mathematical symbol z can indicate or represent the depthof such a two-dimensional, unsorted, unfiltered pressure wavefield as isknown and understood by those skilled in the art 320, the mathematicalsymbol Δz can indicate or represent a preselected depth increment as isknown and understood by those skilled in the art 325, the mathematicalsymbol ω can indicate or represent the temporal frequency of thetwo-dimensional, unsorted, unfiltered pressure wavefield at a particularspatial location within the wavefield as is known and understood bythose skilled in the art 300, the mathematical symbol k_(x) can indicateor represent the transverse wavenumber of the two-dimensional, unsorted,unfiltered pressure wavefield at a particular spatial location withinthe wavefield as is known and understood by those skilled in the art305, the mathematical symbol x′ can indicate or represent the transversecoordinate of a spatial location within the two-dimensional, unsorted,unfiltered pressure wavefield at input as is known and understood bythose skilled in the art 330, the mathematical symbol x can indicate orrepresent the transverse coordinate the transverse coordinate of aspatial location within the two-dimensional, unsorted, unfilteredpressure wavefield at output as is known and understood by those skilledin the art 335, and the mathematical function v(x) can represent thespace-variant velocity field of the unfiltered wavefield at a spatiallocation with the unsorted wavefield as is known and understood by thoseskilled in the art 310.

Accordingly, the kernel of equation (1) can be defined mathematically asa multi-variable function, for example, as:

$\begin{matrix}{\left. {{W\left( {{x - x^{\prime}},{k(x)}} \right)},{\Delta \; z}} \right) = {\frac{1}{2\pi}{\int_{\Re}{{\hat{W}\left( {k_{x},{k(x)},{\Delta \; z}} \right)}^{{- }\; {k_{x}{({x - x^{\prime}})}}}{k_{x}}}}}} & \left( {{equation}\mspace{14mu} 3} \right) \\{{where}{{\hat{W}\left( {k_{x},{k(x)},{\Delta \; z}} \right)} = {{\exp\left( {{\Delta}\; z\sqrt{{k(x)}^{2} - k_{x}^{2}}} \right)}.}}} & \left( {{equation}\mspace{14mu} 4} \right)\end{matrix}$

When the velocity is constant, equation 1 beneficially becomes thespace-frequency equivalent of Gazdag's (1978) phase-shift extrapolation.The nonstationary convolution operator, W, can beneficially handle, forexample, lateral velocity variations by using a different operator foreach spatial lateral location.

As is known and understood by those skilled in the art, the region where|k_(x)|≦|k| is called the propagating waves region, and the region where|k_(x)|>|k| is called the evanescent waves region. Evanescent waves areexponentially decaying with depth, and unwanted coherent seismic noise,such as, ground roll energy or other unwanted energy attributable tosurface waves, falls in this region. Accordingly, the unwanted coherentseismic noise can be filtered out during the extrapolation process.Reconstructing the original wavefield, after removing the noise, can bedone by upward continuing the wavefield back to z according to themathematical function of multiple variables indicated or represented by

$\begin{matrix}{{{\psi \left( {x,z,\omega} \right)} = {\int_{\Re}{{\psi \left( {x^{\prime},{z + {\Delta \; z}},\omega} \right)}{W^{*}\left( {{x - {xi}},{k(x)},{\Delta \; z}} \right)}{x^{\prime}}}}},} & \left( {{equation}\mspace{14mu} 5} \right)\end{matrix}$

where “*” indicates the complex conjugate (equation 6). A complexconjugate, as is known and understood by those skilled in the art, canbe defined as one or a pair of complex numbers, each having the samereal parts but with imaginary parts that differ in sign. For example,the numbers 2+3i and 2−3i are complex conjugates of each other as isknown and understood by those skilled in the art.

A similar, yet more efficient, result can be obtained by insertingequation 1 into equation 5 to obtain a multi-variable mathematicalfunction indicated or represented by

$\begin{matrix}{{{\psi \left( {x,{z + {\Delta \; z}},\omega} \right)} = {\int_{\Re}{{\psi \left( {x^{\prime},z,\omega} \right)}{P\left( {{x - {xi}},{k(x)},{\Delta \; z}} \right)}{x^{\prime}}}}},} & \left( {{equation}\mspace{14mu} 7} \right) \\{{where}{{P\left( {{x - x^{\prime}},{k(x)},{\Delta \; z}} \right)} = {\int_{\Re}{{W\left( {{x - x^{\prime}},{k(x)},{\Delta \; z}} \right)}{W^{*}\left( {{x - x^{\prime}},{k(x)},{\Delta \; z}} \right)}{{x^{\prime}}.}}}}} & \left( {{equation}\mspace{14mu} 8} \right)\end{matrix}$

Expressing equation 6 in the wavenumber form provides a multi-variablemathematical function indicated or represented by

$\begin{matrix}{{P\left( {{x - {xi}},{k(x)},{\Delta \; z}} \right)} = {\frac{1}{2\pi}{\int_{\Re}{{{\overset{\Cap}{W}\left( {k_{x},{k(x)},{\Delta \; z}} \right)}}^{2}^{{- }\; {k_{x}{({x - x^{\prime}})}}}{{k_{x}}.}}}}} & \left( {{equation}\mspace{14mu} 9} \right)\end{matrix}$

According to an exemplary embodiment of the present invention, thenonstationary convolution operator P (equation 8), does not have anyphase information but can, for example, handle strong lateral variation.The nonstationary convolution operator (equation 8) can also exclude,for example, both the thin lens and focusing terms and can only performlocalized filtering using the velocity information at each spatiallateral position. The noise removed by equation 8, according to anembodiment of the present invention, is similar to the noise removedafter the backward and forward extrapolation technique employed in somecurrently-existing seismic image filters, but the overall filteringprocess using equation 8 is much more efficient than other filteringprocesses because only a single extrapolation is required and theunfiltered data can remain unsorted.

The nonstationary convolution operators (equation 8) designed byequation 7, according to various exemplary embodiments of the presentinvention, can be, for example, infinitely long. Using simple windowfunctions to truncate such nonstationary convolution operators issuboptimal and can lead, for example, to numerically unstable operators.For noise suppression application, the numerical instability is lesspronounced than in depth imaging because the number of depth steps isrelatively small. That is, the wavefield only needs to be extrapolatedto a depth level that is just below the propagation zone of the unwantedseismic noise in order to filter the unfiltered seismic image data.

Numerical instability is a major problem of seismic image filtersemploying extrapolation processes, but various embodiments of thepresent invention are capable of designing stable wavefieldextrapolators. According to an exemplary embodiment of the presentinvention, the nonstationary convolution operator (equation 8) can bedesigned, for example, using a weighted least squares with a transitionband approach as is known and understood by those skilled in the art. Inthe presence of complex near surface geology, including, for example,rugged topography or complex geological structures, seismic surfacewaves can have complicated wave paths and lateral velocity variations.Accordingly, noise attenuation systems, machines, computer readableprogram products, and associated methods, according to various exemplaryembodiments of the present invention, must be able to handle the stronglateral velocity variation of the seismic wavefield. Generally,wavefield extrapolation methods are powerful in handling lateralvelocity variations; however, the stability of the wavefieldextrapolators can be an important issue when designing wavefieldextrapolators. The stability problem can arise, for instance, due to thepresence of discontinuities at boundaries separating the wavelike andevanescent regions of a wavefield.

Least squares methods can be used, for example, to design wavefieldextrapolators that practically remain stable in a recursive scheme byminimizing the squared error between desired and actual data, ortransforms. Least squares methods can be classified into three majorcategories: (1) unweighted least squares followed by a windowingfunction applied in the space-frequency domain, (2) weighted leastsquares using a smooth transition function connecting the wavefield andevanescent regions, and (3) weighted least squares using a transitionband, i.e., applying zero weight to select data points, for thetransition region. Various embodiments of the present invention applythe third approach which removes a select region, called a transitionband, from the extrapolation function. Using a transition band in theweighted least squares filter design can lead to a more stable designthan using a transition function, such as a spline, for the transitionregion.

More particularly for wavefield extrapolators to function adequately,the amplitude and phase of such wavefield extrapolators, in thewavenumber domain, often must match the amplitude and phase of the exactspectrum in the wavelike region, and be only less than unity in theevanescent region. When using a weighted least squares with a transitionapproach to design nonstationary convolution operators according tovarious embodiments of the present invention, however, the extrapolatordesign problem can be made much more flexible through the introductionof a transition region between the wavelike and evanescent regions. Sucha formulation fits the way filter specifications are usually given muchmore efficiently than designating one wavenumber to specify the boundarybetween the wavelike and the evanescent regions. More over, using aweighted least squares with a transition band approach according tovarious embodiments of the present invention beneficially minimizes theGibbs phenomenon, and the approximation in the wavelike and evanescentregions can be dramatically improved.

The weighted least squares approach beneficially employs a transitionfunction. Particular a spline function can be constructed that goes froma mathematical variable k_(α) to the Nyquist wavenumber indicated orrepresented by π/Δx. In such a case, the evanescent region of theunfiltered wavefield becomes the transition region. Furthermore, thedesired spectrum, indicated or represented by Ŵ_(D), does not have theslope discontinuities that are present in the exact spectrum, indicatedor represented by Ŵ, which can cause an inaccurate approximation. Anextrapolator stabilized using a weighted least squares with a transitionband approach can be obtained using a mathematical function indicated orrepresented by {tilde over (W)}=[F ^(H) Y F]⁻¹ F ^(H) Y{circumflex over(W)}_(D).

Using a transition region in the desired spectrum can significantlyreduce the Gibbs phenomenon and give greater control over the designprocess. The transition region, for example, allows for a smoothtransition between the wavelike and evanescent regions of the unfilteredwavefield. One of the most effective modifications of the least squareserror design methods is to change the band of wavenumbers over which theminimization is carried out. The band of wavenumbers for the transitionband can, for example, be simply removed from the error definition. Thisregion can be referred to as the transition band or “don't care” region.Beneficially, in the weighted least squares using a transition bandapproach according to various embodiments of the present invention, thedesired spectrum is the exact spectrum. That is, the exact spectrum isnot modified by using a transition function as was the case in a simpleweighted least squares approach. Rather, the weighted least squares witha transition band approach according to various embodiments of thepresent invention uses a different weight function that can be definedas:

${\overset{\sim}{Y}\left( k_{x} \right)} = \left\{ \begin{matrix}{1;} & {{k_{x}} \leq k_{\alpha}} \\{0;} & {k_{\alpha} < {k_{x}} < {{{2k} - k_{\alpha}}}} \\{ɛ;} & {{{{2k} - k_{\alpha}}} < {k_{x}} < \frac{\pi}{\Delta \; x}}\end{matrix} \right.$

The region k_(α)<|k_(x)|<|2k−k_(α)| is called the transition band, whereit is excluded from the error measure by giving it a weight value ofzero. Accordingly, a weighted least squares with a transition bandconvolution operator according to an exemplary embodiment of the presentinvention can then be designed using {tilde over (W)}=[F ^(H) Y F]⁻¹ F^(H){tilde over (Y)}Ŵ. Such an approach, should yield a smaller squarederror and a greater reduction of overshoot than should be expected usinga transition function because there is no constraint placed on the exactspectrum, Ŵ, in the transition region.

As is perhaps best illustrated in FIG. 5 and FIG. 8, the above describedmathematical functions and operators can be used as a part of computerimplemented methods, systems, machines, and computer readable programproducts, according to various embodiments of the present invention, togenerate filtered seismic image data through a single extrapolation byconstructing a plurality of nonstationary convolution operators toperform localized filtering at each of a plurality of spatial locationsof a two-dimensional unsorted, unfiltered pressure wavefield constructedfrom unfiltered seismic image data. A computer implemented methodaccording to an exemplary embodiment of the present invention caninclude, for example, the steps of receiving from a seismic imagereceiver at a recording surface a plurality of seismic energy signalsthat have propagated throughout a two-dimensional surface wavepropagation zone (block 200), converting the plurality of seismic energysignals received from the seismic energy receiver into unfiltered,unsorted seismic image data (block 205), constructing, based on theplurality of unfiltered, unsorted seismic image data, a two-dimensional,unsorted, unfiltered pressure wavefield including a plurality of spatiallocations each defined by a transverse coordinate and a depth coordinate(block 210), and locating a selected one of the plurality of spatiallocations at a point where the depth level coordinate of the selectedone of the plurality of spatial locations is equal to a depth levelcoordinate of the recording surface and the transverse coordinate of theselected one of the plurality of spatial locations is equal to atransverse coordinate of a first transverse boundary of thetwo-dimensional surface wave propagation zone (block 215).

As is perhaps illustrated best in FIG. 8, such a computer implementedaccording to an exemplary embodiment of the present invention canfurther include the steps of:

(a) determining, for the selected one of the plurality of spatiallocations within the two-dimensional, unsorted, unfiltered pressurewavefield, a space-variant velocity (indicated or represented by v(x))(block 310) based on the transverse coordinate (block 215, 330) of theselected one of the plurality of spatial locations (indicated orrepresented by x′);

(b) determining, responsive to determining the space-variant velocity(v(x)) (block 310), for the selected one of the plurality of spatiallocations within the two-dimensional, unsorted, unfiltered pressurewavefield, a quotient of a temporal frequency of the selected one of theplurality of spatial locations (indicated or represented by ω) (block300) and the space-variant velocity of the selected one of the pluralityof spatial locations (v(x)) (block 310) to thereby define a mathematicalfunction indicated or represented by k(x) (equation 2);

(c) determining responsive to determining k(x) (equation 2), for theselected one of the plurality of spatial locations within thetwo-dimensional, unsorted, unfiltered pressure wavefield, an exponentialfunction of a product of (i) a square root of negative one (indicated orrepresented by the imaginary number, i), (ii) a preselected wavefielddepth increment (indicated or represented by Δz) (block 325), and (iii)a square root of (1) a square of a transverse wavenumber of the selectedone of the plurality of spatial locations(indicated or represented byk_(x)) (block 305) subtracted from (2) a square of k(x) (√{square rootover (k(x)²−k_(x) ²)}), to thereby define a multi-variable mathematicalfunction indicated or represented by Ŵ(k_(x), k(x), Δz) (equation 4);

(d) determining responsive to determining Ŵ(k_(x), k(x), Δz) (equation4), for the selected one of the plurality of spatial locations withinthe two-dimensional, unsorted, unfiltered pressure wavefield, a productof (i) a quotient of one and a product of two and pi (indicated orrepresented by π)

$\left( \frac{1}{2\pi} \right),$

and (ii) an integral over a set of real numbers, (indicated orrepresented by

), with respect to the transverse wavenumber of the selected one of theof the plurality of spatial locations (k_(x)) (block 305), of a productof Ŵ(k_(x), k(x), Δz) (equation 4) and an exponential function of: (1) aproduct of negative square root of negative one (indicated orrepresented by the imaginary number, i), (2) the transverse wavenumberof the selected one of the plurality of spatial locations (k_(x)) (block305), and (3) a difference between the transverse coordinate of theselected one of the plurality of spatial locations (indicated orrepresented by x′) (block 215,330) and a transverse coordinate of asecond one of the plurality of spatial locations (indicated orrepresented by x) (block 220, 335) where the second one of the pluralityof spatial locations is located at a point closer to a second transverseboundary of the two-dimensional surface wave propagation zone than theselected one of the plurality of spatial locations

$\left( {\frac{1}{2\pi}{\int_{\Re}{{\hat{W}\left( {k_{x},{k(x)},{\Delta \; z}} \right)}^{{- }\; {k_{x}{({x - x^{\prime}})}}}{k_{x}}}}} \right),$

to thereby define a multi-variable mathematical function indicated orrepresented by W(x-x′, k(x), Δz) (equation 3);

(e) determining responsive to determining W(x-x′, k(x), Δz) (equation3), a complex conjugate of W(x-x′, k(x), Δz) (equation 3) to therebydefine a multi-variable mathematical function indicated or representedby W*(x-x′, k(x), Δz) (equation 6);

(f) building responsive to determining W(x-x′, k(x), Δz) (equation 3)and determining W*(x-x′, k(x), Δz) (equation 6), a nonstationaryconvolution operator for the selected one of the plurality of spatiallocations within the two-dimensional, unsorted, unfiltered pressurewavefield by taking an integral over a set of real numbers (

), with respect to the transverse coordinate of the selected one of theplurality of spatial locations (x′) (block 215, 330), of a product ofW(x-x k(x), Δz) (equation 3) and W*(x-x′, k(x), Δz) (equation 6) tothereby define a multi-variable mathematical function indicated orrepresented by P(x-x′, k(x), Δz) (equation 8);

(g) extrapolating the two-dimensional, unsorted, unfiltered pressurewavefield at the selected one of the plurality of spatial locationswithin the two-dimensional, unsorted, unfiltered pressure wavefield(block 215, 330) using the nonstationary convolution operator for theselected one of the plurality of spatial locations built by the computer(equation 8) by taking an integral over a set of real numbers (

) of a product of P(x-x′, k(x), Δz) (equation 8) and thetwo-dimensional, unsorted, unfiltered pressure wavefield (indicated orrepresented by Ψ(x, z+Δz, ω)

(∫_(ℜ)ψ(x^(′), z, ω)P(x − xi, k(x), Δ z)x^(′))

(block 35), to thereby perform localized filtering of the selected oneof the plurality of spatial locations;

(h) setting the transverse coordinate of the selected one of theplurality of spatial locations (x′) equal to the transverse coordinateof the second one of the plurality of spatial locations (x) (block 235);

(i) repeating steps (a) through (h) until the transverse coordinate ofthe second one of the plurality of spatial locations (x) equals orexceeds the transverse coordinate of the second transverse boundary ofthe two-dimensional surface wave propagation zone (block 235);

(j) increasing the depth level coordinate (z) by the preselectedwavefield depth increment (Δz) (block 240);

(k) setting the transverse coordinate of the selected one of theplurality of spatial locations (k_(x)) equal to the transversecoordinate of the first boundary of the two-dimensional surface wavepropagation zone (block 215, 330); and

(l) repeating steps (a) through (k) until the depth level coordinate (z)is equal to a depth below the two-dimensional surface wave propagationzone of the plurality of seismic energy signals (block 240) to therebygenerate filtered seismic image data (block 65) that when processedfurther by the computer can create a filtered seismic image to bedisplayed on a display adapted to be in communication with the computer,each repetition of steps (a) through (k) being defined as an iteration.

Furthermore, step of building the nonstationary convolution operator forthe selected one of the plurality of spatial locations within thetwo-dimensional, unsorted, unfiltered pressure wavefield can furtherinclude, for example, the step of stabilizing the nonstationaryconvolution operator using a weighted least squares with a transitionband approach as is known and understood by those skilled in the art.Furthermore, the step of constructing a two-dimensional unfilteredpressure wavefield can further include, for example, the step ofperforming a Fourier transformation of the two-dimensional unfilteredpressure wavefield over a temporal coordinate. Additionally, accordingto an embodiment of the present invention, the computer implementedmethod can further include the steps of generating at each iteration,filtered seismic image data responsive to extrapolating thetwo-dimensional unfiltered pressure wavefield at the selected one of theplurality of spatial locations within the two-dimensional unfilteredpressure wavefield, and processing the filtered seismic image datagenerated at each iteration to thereby create a human-readable filteredseismic image to be transmitted to an output device adapted to be incommunication with the computer.

Moreover, such a computer implemented method according to an embodimentof the present invention can further include the steps of storing theunfiltered, unsorted seismic image data in a first database positionedto be in communication with the computer, storing the two-dimensionalunfiltered pressure wavefield in a second database positioned to be incommunication with the computer, storing, at each iteration, thefiltered seismic image data in a third database positioned to be incommunication with the computer, storing the filtered seismic image in afourth database positioned to be in communication with the computer;processing the filtered seismic image data to create a human-readablefiltered seismic image; and transmitting the filtered seismic image toan output device positioned to be in communicated with the computer.Each aforementioned step of any method according to an embodiment of thepresent invention can be performed by a computer in one or more computerprocesses, and the steps of any particular method according to anexemplary embodiment of the present invention can all be performed bythe computer in a one computer process or can each be performed by thecomputer in one or more separate computer processes.

As is perhaps best illustrated in FIG. 9, various embodiments of thepresent invention can also provide a seismic image filtering machine tocreate a filtered seismic image responsive to filtered seismic imagedata generated by attenuating coherent seismic noise from surface wavesof an unfiltered wavefield constructed from unfiltered seismic imagedata through a single downward extrapolation of the unfiltered wavefieldusing a plurality of nonstationary convolution operators to performlocalized filtering at each of a plurality of spatial locations of theunfiltered wavefield. Particularly, FIG. 9 illustrates, using ahigh-level schematic block flow diagram, the use of such a seismic imagefiltering machine according to various exemplary embodiments of thepresent invention. Generally, a seismic energy source (block 10) can bepositioned to propagate seismic energy signals into a propagation zone(block 80). Such seismic energy can include any seismic or acousticenergy whether from an explosive, implosive, swept-frequency, or randomsources. Furthermore, a seismic energy receiver (block 20) can bepositioned to receive and record seismic energy data or seismic fieldrecords in any form, including but not limited to, a geographical timeseries recording of the acoustic reflection and refraction of waveformsthat travel from the seismic energy source (block 10) to the seismicenergy receiver (block 20). Variations in the travel times of reflectionand refraction events in one or more field records in seismic dataprocessing can produce a seismic image, defined by unfiltered seismicimage data, that demonstrates subsurface structure according to anexemplary embodiment of the present invention. Beneficially, such aseismic image can be used to aid in the search for, and exploitation of,subsurface mineral deposits; however, in order for the seismic image tobe of the greatest functionality, it must first be filtered.

Accordingly, according to various embodiments of the present invention,such a seismic image can be beneficially filtered, for example, using aseismic image filtering machine (block 400). According to an exemplaryembodiment of the present invention, a seismic filtering machine (block400) can use a nonstationary seismic image filter that is implemented inthe space-frequency domain and includes nonstationary convolutionoperator designed using a weighted least squares with a transition bandapproach. Such a seismic image filtering machine (block 400) can beconfigured according to an exemplary embodiment of the presentinvention, for example, to attenuate coherent seismic energy, or noise,from seismic images. Particularly, such a seismic image filteringmachine (block 400), according to an exemplary embodiment of the presentinvention, can apply a nonstationary convolution operator to downwardlycontinue unfiltered seismic image data that defines an unfilteredseismic image to a depth level below the propagation zone to generatenew filtered seismic image data that, when processed by the computer andtransmitted to a display adapted to be in communication with thecomputer, creates a filtered seismic image.

As is perhaps best illustrated in FIG. 9, such a seismic image filteringmachine 400 according to various exemplary embodiments of the presentinvention can include, for example, a first database 422 storingunfiltered, unsorted seismic image data derived from a plurality ofseismic energy signals received from a seismic energy receiver at arecording surface after propagating throughout a surface wavepropagation zone, and a computer 410 adapted to be in communication withthe first database 422 and having at least a processor 416 and memory412. A seismic image filtering machine 400 can also include, forexample, an unfiltered wavefield constructor computer readable programproduct 430 stored in a tangible computer readable storage medium andincluding instructions that, when executed by the computer 410, causethe computer 410 to perform the operation of constructing an unfilteredwavefield delineated by a plurality of spatial locations from theunfiltered, unsorted seismic image data stored in the first database422. Moreover such a seismic image filtering machine can furtherinclude, for example, a nonstationary convolution operator buildercomputer readable program product 431 stored in a tangible computerreadable storage medium and including instructions that, when executedby the computer 410, cause the computer 410 to perform the operation ofbuilding, responsive to the unfiltered wavefield constructer computerreadable program product 430, a plurality of nonstationary convolutionoperators, one for each of the plurality of spatial locations of theunfiltered wavefield, each of the nonstationary convolution operatorsbeing based on the coordinate location of each of the plurality ofspatial locations of the unfiltered wavefield and a space-variantvelocity, temporal frequency, transverse wavenumber, and wavelength ofthe unfiltered wavefield at each spatial location.

Also according to various exemplary embodiments of the presentinvention, a seismic image filtering machine 400 can also include anonstationary convolution operator stabilizer computer readable programproduct 432 stored in a tangible computer readable storage medium andincluding instructions that, when executed by the computer 410, causethe computer 410 to perform the operation of stabilizing each of thenonstationary convolution operators using a weighted least squares witha transition band approach as is known and understood by those skilledin the art. Beneficially, such a seismic image filtering machine canfurther include, for example, a localized filter computer readableprogram product 434 stored in a tangible computer readable storagemedium and including instructions that, when executed by the computer410, cause the computer 410 to perform the operation of locallyfiltering each of the plurality of spatial locations of the unfilteredwavefield using, at each spatial locations, at least one of theplurality of nonstationary convolutions operators associated with thatone of the plurality of spatial locations to thereby effectuate a singledownward extrapolation of the unfiltered wavefield. Furthermore, aseismic image filtering machine can include, for example, a filteredseismic image creator computer readable program product 436 stored in atangible computer readable storage medium and including instructionsthat, when executed by the computer 410, cause the computer 410 toperform the operation of creating a filtered seismic image responsive tofiltered seismic image data generated by filtering, in the localizedfilter computer readable program product 434, the unfiltered wavefieldat each of the plurality of spatial locations of the unfilteredwavefield.

Beneficially, a seismic image filtering machine 400, according tovarious embodiments of the present invention can also include, by way ofexample, a display 414, a second database 424, a third database 428, anda fourth database 426, each adapted to be in communication with thecomputer. Additionally, the unfiltered wavefield constructor computerreadable program product 430 can, for example, further includeinstructions that, when executed by the computer 410, cause the computer410 to perform the operation of storing the unfiltered wavefield in thesecond database 424. Similarly, the localized filter computer readableprogram product 434 can further include, for example, instructions that,when executed by the computer 410, cause the computer 410 to perform theoperation of storing the filtered seismic image data in the thirddatabase 428. The filtered seismic image creator computer readableprogram product 436 can also include, for example, instructions that,when executed by the computer 410, cause the computer 410 to perform theoperation of storing the filtered seismic image in the fourth database426. Furthermore, a seismic image filtering machine 400, according to anexemplary embodiment of the present invention can further include afiltered image displayer computer readable program product 438 stored ina tangible computer readable storage medium and including instructionsthat, when executed by the computer 410, cause the computer 410 toperform the operation of displaying the filtered seismic image on thedisplay 414 responsive to converting the filtered seismic image datainto a graphic image capable of being displayed on the display inhuman-readable form.

Also according to exemplary embodiments of the present invention, eachof the of the plurality of nonstationary convolution operators built bythe nonstationary convolution operator builder computer readable programproduct 431 can be beneficially different from each of the others of theplurality of nonstationary convolution operators and can be, forexample, uniquely associated with one of the plurality of spatiallocations of the unfiltered wavefield. Moreover, the operation offiltering by the localized filter computer readable program product 434can be implemented, for example, in one of, or both, a seismic energysource domain or a seismic energy receiver domain. Additionally, thepropagation zone, as is known and understood by those skilled in theart, can include complex geology and rugged topography, and theunfiltered wavefield can include coherent seismic noise in the form ofevanescent waves that have propagated throughout the surface waveproposition zone in complicated wave paths due to the complex geologyand rugged topography within the propagation zone.

Beneficially, the nonstationary convolution operator builder computerreadable program product 431 further includes instructions that, whenexecuted by the computer 410, cause the computer 410 to perform theoperations of determining, for a selected one of the plurality ofspatial locations within the unfiltered wavefield, a space-variantvelocity (indicated or represented by v(x)), determining, for theselected one of the plurality of spatial locations within the unfilteredwavefield, a quotient of a temporal frequency (indicated or representedby (p) and the space-variant velocity of the selected one of theplurality of spatial locations to thereby define a mathematical functionindicated or represented by k(x), and determining, for the selected oneof the plurality of spatial locations within the unfiltered wavefield,an exponential function of a product of (i) a square root of negativeone (indicated or represented by the imaginary number, i), (ii) apreselected wavefield depth increment (indicated or represented by Δz),and (iii) a square root of (1) a square of a transverse wavenumber(indicated or represented by k_(x)) of the selected one of the pluralityof spatial locations subtracted from (2) a square of k(x) (√{square rootover (k(x)²−k_(x) ²)}), to thereby define a multi-variable mathematicalfunction indicated or represented by Ŵ(kx, k(x),

z). The nonstationary convolution operator builder computer readableprogram product 431 can also include instructions that, when executed bythe computer 410, cause the computer 410 to perform the operation ofdetermining, for the selected one of the plurality of spatial locationswithin the unfiltered wavefield, a product of (i) a quotient of one anda product of two and pi (indicated or represented by π)

$\left( \frac{1}{2\pi} \right),$

and (ii) an integral over a set of real numbers (indicated orrepresented by

) with respect to a transverse wavenumber of the selected one of the ofthe plurality of spatial locations (k_(x)), of a product of Ŵ(kx, k(x),Δz) and an exponential function of: (1) a product of negative squareroot of negative one (indicated or represented by the imaginary number,i), (2) the transverse wavenumber of the selected one of the pluralityof spatial locations (k_(x)), and (3) a difference between thecoordinate location of the selected one of the plurality of spatiallocations (indicated or represented by x′) and a coordinate location ofa second one of the plurality of spatial locations (indicated orrepresented by x), to thereby define a multi-variable mathematicalfunction indicated or represented by W(x-x′, k(x), Δz). Furthermore,such a nonstationary convolution operator builder computer readableprogram product 431 according to an exemplary embodiment of the presentinvention can further include, for example, instructions that, whenexecuted by the computer 410, cause the computer to perform theoperation of determining an integral over a set of real numbers (

), with respect to the coordinate location of the selected one of theplurality of spatial location (indicated or represented by x′), of aproduct of W(x-x′, k(x), Δz) and a complex conjugate of W(x-x′, k(x),Δz) to thereby build a nonstationary convolution operator.

Moreover, a localized filter computer readable program product 434, canfurther include, for example, instructions that, when executed by thecomputer 710, cause the computer 710 to perform the operation ofdownward continuing the unfiltered wavefield at each of the plurality ofspatial locations of the unfiltered wavefield to a depth level below thesurface wave propagation zone of the seismic energy signals.Additionally, according to various exemplary embodiments of the presentinvention, the unfiltered wavefield constructed by the unfilteredwavefield constructor computer readable program product 430 can beFourier transformed over a temporal coordinate prior to its use by aseismic image filtering machine 400. Furthermore, the localized filtercomputer readable program product 434 can further include, for example,instructions that when executed by the computer 410 cause the computer410 to perform the operation of generating, for each of the plurality ofspatial locations of the unfiltered wavefield, filtered seismic imagedata responsive to filtering each of the plurality of spatial locations.Accordingly, the filtered seismic image created by filtered seismicimage creator computer readable program product 436 can be based, forexample, on the filtered seismic image data.

As is perhaps best illustrated in FIG. 11, various exemplary embodimentsof the present invention also provide a system to generate a filteredseismic image responsive to seismic image data filtered by attenuatingcoherent seismic noise from surface waves of an unfiltered wavefieldconstructed from the seismic image data using a plurality ofnonstationary convolution operators to perform localized filtering ateach of a plurality of spatial locations of the unfiltered wavefield.Such a system can include, for example, a tangible computer readablemedium storing unfiltered seismic image data 35 and a computer 405including at least a memory 412, a display 414, a processor 416, and acomputer readable storage medium 420. The memory can further include,for example, a first database 422 to store unfiltered seismic imagedata, a second database 424 to store an unfiltered wavefield, a thirddatabase 428 to store filtered seismic image data, and a fourth database426 to store a filtered seismic image capable of being displayed inhuman-readable form on the display 414 adapted to be in communicationwith the computer 405. The memory of the computer can further include,for example, an unfiltered wavefield constructor 440, a nonstationaryconvolution operator builder 441, a nonstationary convolution operatorstabilizer 442, a localized filter 444, a filtered seismic imagegenerator 446, and a filtered image displayer 448. Generally, such asystem, according to various embodiments of the present invention,receives as input unfiltered seismic image data 35 and returns as outputto a display a filtered seismic image 70.

More particularly, the unfiltered wavefield constructor 440 can beconfigured, for example, to construct an unfiltered wavefield delineatedby a plurality of spatial locations from the unfiltered, unsortedseismic image data stored in the first database 442. Additionally, thenonstationary convolution operator builder 441 can, for example, beconfigured to build, responsive to the unfiltered wavefield constructer440, a plurality of nonstationary convolution operators, one for each ofthe plurality of spatial locations of the unfiltered wavefield, each ofthe nonstationary convolution operators being based on a coordinatelocation of each of the plurality of spatial locations of the unfilteredwavefield and the space-variant velocity, temporal frequency, transversewavenumber, and wavelength of the unfiltered wavefield at each spatiallocation. By way of example, the nonstationary convolution operatorstabilizer 442 can be configured to stabilize each of the nonstationaryconvolution operators using a weighted least squares with a transitionband approach. Also according to various exemplary embodiments of thepresent invention, the localized filter 444 can be, for example,configured to locally filter each of the plurality of spatial locationsof the unfiltered wavefield using, at each spatial locations, at leastone of the plurality of nonstationary convolutions operators associatedwith that one of the plurality of spatial locations to therebyeffectuate a single downward extrapolation of the unfiltered wavefield.Moreover, the filtered seismic image generator 446 can, for example, beconfigured to generate a filtered seismic image responsive to filteredseismic image data generated by the localized filter at each of theplurality of spatial locations of the unfiltered wavefield, and thefiltered image displayer 448 can be, for example, configured to displaythe filtered seismic image on the display 414.

As is perhaps best illustrated by FIGS. 11 through 21, various exemplaryembodiments of the present invention can filter unfiltered seismicimages to produce high-quality filtered seismic images. For example,FIG. 12 shows an unfiltered seismic image, specifically, a shot gather,produced using a synthetic dataset modeled over complex geology andrough topography, according to an embodiment of the present invention.In FIG. 12, for example, the receiver spacing is eight (8) meters andthe depth step is eight (8) meters. FIG. 13 shows a seismic image,specifically, a shot gather, filtered according to an embodiment of thisinvention. In this example produced using a synthetic dataset accordingto an exemplary embodiment of the present invention, the correctvelocity model was used, and the unfiltered seismic data 35 wasextrapolated to a depth three-hundred (300) meters below the propagationzone. The filtered seismic image in FIG. 13 illustrates that most of thecoherent seismic energy has been attenuated by the nonstationary seismicimage data filter 40 according to an exemplary embodiment of the presentinvention. The noise removed by the filter, calculated by subtractingthe filtered seismic image data 65 from the unfiltered seismic imagedata 35, is shown in FIG. 14. Beneficially, FIG. 14 shows that theremoved seismic energy, or coherent seismic noise, excludes desiredseismic reflection events thus demonstrating the effectiveness of aseismic filter according to an various embodiments of the presentinvention.

Various embodiments of the present invention also achieve beneficialresults, for example, when applied to real, as opposed to synthetic,datasets. For example, FIG. 15 shows a near surface velocity model of areal dataset, where refraction tomography was used, acquired from anirregular surface with near surface velocity variations, according to anembodiment of the present invention. The dashed line 500 indicates thedatum to which the data are extrapolated. Furthermore, FIG. 16 shows anunfiltered seismic image, specifically, a shot gather, produced using areal dataset acquired from an irregular surface with near surfacevelocity variations. FIG. 17 shows the same seismic image as shown inFIG. 16 after it is filtered according to an embodiment of the presentinvention. The noise removed by the filter, calculated by subtractingthe filtered seismic image data from the unfiltered seismic image data,is shown in FIG. 18. FIG. 18 demonstrates that various embodiments ofthe present invention are effective in attenuating most of the unwantedseismic energy, including, for example, direct arrival and ground roll,without removing the desired seismic reflection energy.

Beneficially, for example, the present invention results in improvedimage quality for both shallow and deep geological formations. Forinstance, FIGS. 18 and 19, respectively, show a seismic image,specifically, a seismic stack result, produced using real datasetacquired from a complex, shallow geological formation with and withoutfiltering according to embodiments of the present invention. Theelevation profile 510, in meters, showing rough topography, is displayedat the top each of FIGS. 18 and 19. Arrows in FIG. 20 520 indicate areasof improved image quality and illustrate that the image in FIG. 20 hasmore visible details and focused reflection events than the resultillustrated in FIG. 19. Various embodiments of the present inventionalso produce, for example, enhanced image quality results for deepgeological formations. FIGS. 20 and 21, respectively, show a seismicimage, specifically, a seismic stack result, produced using a realdataset acquired from a complex, deep geological formation with andwithout filtering according to the present invention. The elevationprofile 530, in meters, showing rough topography, is displayed at thetop each of FIGS. 20 and 21. Arrows in FIG. 22 540 indicate areas ofimproved image quality and show that the image illustrated in FIG. 22has more visible details and focused reflection events than the resultillustrated in FIG. 21.

It is important to note that while embodiments of the present inventionhave been described in the context of a fully functional system, thoseskilled in the art will appreciate that the mechanism of at leastportions of the present invention or aspects thereof are capable ofbeing distributed in the form of a computer readable program productstored in a tangible computer readable storage medium and a computerreadable medium of instructions in a variety of forms for execution on aprocessor, processors, or the like, and that the present inventionapplies equally regardless of the particular type of signal bearingmedia used to actually carry out the distribution. Note, the computerreadable program product can be in the form of microcode, programs,routines, and symbolic languages that provide a specific set or sets ofordered operations that control the functioning of the hardware anddirect its operation, as known and understood by those skilled in theart.

Note, the computer 405, 410, shown schematically in FIG. 10 and FIG. 11,represents a computer or computer cluster or computer farm and are notlimited to any individual physical computers. The number of computersalong with associated storage capacity and their architecture andconfiguration can be increased based on usage, demand, and capacityrequirements for the system. Also note, the memory 412 can includevolatile and nonvolatile memory known to those skilled in the artincluding, for example, RAM, ROM, and magnetic or optical disks, just toname a few. Additionally, examples of tangible computer readable storagemedium include but are not limited to: nonvolatile hard-coded type mediasuch as read only memories (ROMs), CD-ROMs, and DVD-ROMs, or erasable,electrically programmable read only memories (EEPROMs), recordable typemedia such as floppy disks, hard disk drives, solid state disk drives,hard disk RAIDs, direct attached storage devices, CD-R/RWs, DVD-RAMs,DVD-R/RWs, DVD+R/RWs, flash drives, memory sticks, HD-DVDs, mini disks,laser disks, Blu-ray disks, and other newer types of memories, andtransmission type media such as digital and analog communication linksas are known and understood by those skilled in the art. Noteadditionally, the processor 416 is not limited to any single processoror processor type and can include any number of central processingunits, microprocessors, graphics processing units, digital signalprocessors, network processors, coprocessors, data processors, audioprocessors, and any other electronic circuits that can evaluate computerreadable instructions as is known and understood to those skilled in theart.

Embodiments of the present invention include several advantages. Forexample, embodiments of the present invention can be sufficiently robustto handle strong lateral velocity variation of seismic surface wavesthereby making the present invention an effective tool to attenuatecomplicated coherent seismic noise. Additionally, embodiments of thepresent invention, for example, can effectively attenuate coherentseismic noise even over rough topography or complex near surfacegeology. Moreover a coherent seismic noise filter, according to variousembodiments of the present invention, for example, can be implemented ineither the seismic source or seismic receiver domains, and the coherentseismic noise filter, for example, can attenuate complicated coherentseismic noise more quickly and efficiently than current systems andmethods. Unlike current seismic filtering systems and methods whichrequire multiple data extrapolation processes and a sorted data set,embodiments of the present invention can, for example, enhance the speedand efficiency of current seismic filters by reducing the process stepsnecessary to filter a seismic image.

In the drawings and specification, there have been disclosed a typicalpreferred embodiment of the invention, and although specific terms areemployed, the terms are used in a descriptive sense only and not forpurposes of limitation. Various embodiments of the invention have beendescribed in considerable detail with specific reference to thesevarious illustrated embodiments. It will be apparent, however, thatvarious modifications and changes can be made within the spirit andscope of the invention as described in the foregoing specification andas defined in the appended claims.

1. A computer implemented method to generate a filtered seismic image ona display, the computer implemented method comprising: constructing, bya computer in a first computer process, an unfiltered wavefielddelineated by a plurality of spatial locations from unfiltered, unsortedseismic image data generated responsive to a plurality of seismic energysignals propagated through a surface wave propagation zone; building, bythe computer in a second computer process, a plurality of nonstationaryconvolution operators, one for each of the plurality of spatiallocations of the unfiltered wavefield, responsive to constructing theunfiltered wavefield in the first computer process for each of theplurality of spatial locations of the unfiltered wavefield, each of theplurality of nonstationary convolution operators being different fromothers of the plurality of nonstationary convolution operators anduniquely associated with one of the plurality of spatial locations ofthe unfiltered wavefield; extrapolating, by the computer in a thirdcomputer process, responsive to building each of the plurality ofnonstationary convolution operators, the unfiltered wavefield at each ofthe plurality of spatial locations of the unfiltered wavefield to adepth level below the surface wave propagation zone of the seismicenergy signals, to thereby locally filter each of the plurality ofspatial locations of the unfiltered wavefield; and generating, by thecomputer in a fourth computer process, a filtered seismic image on adisplay, adapted to be in communication with the computer, responsive toeach of the plurality of spatial locations of the unfiltered wavefieldlocally filtered by the computer in the third computer process.
 2. Thecomputer implemented method of claim 1, wherein the method to generate afiltered seismic image on a display is further responsive to seismicimage data filtered by attenuating coherent seismic noise from surfacewaves of an unfiltered wavefield through a single downward extrapolationusing specially-constructed nonstationary convolution operators toperform localized filtering at each of a plurality of spatial locationsof the unfiltered wavefield.
 3. The computer implemented method of claim1, wherein each of the plurality of nonstationary convolution operatorsbeing based on a coordinate location of each of the plurality of spatiallocations of the unfiltered wavefield within the unfiltered wavefield,and a space-variant velocity, temporal frequency, transverse wavenumber,and wavelength of the unfiltered wavefield at each of the plurality ofspatial locations.
 4. The computer implemented method of claim 3,wherein each of the plurality of nonstationary convolution operators,one for each of the plurality of spatial locations of the unfilteredwavefield, are built by performing an inverse Fourier transformationover the transverse wavenumber coordinate of a power of a phase shiftoperator at each of the plurality of spatial locations of the unfilteredwavefield; and wherein the step of extrapolating, by the computer in thethird computer process responsive to building each of the plurality ofnonstationary convolution operators is implemented in one of, or both, aseismic energy source domain or a seismic energy receiver domain.
 5. Thecomputer implemented method of claim 3, whereby the building, by thecomputer in a second computer process, a plurality of nonstationaryconvolution operators, one for each of the plurality of spatiallocations of the unfiltered wavefield, responsive to constructing theunfiltered wavefield in the first computer process for each of theplurality of spatial locations of the unfiltered wavefield, furtherincludes: determining, by the computer in a fifth computer process, fora selected one of the plurality of spatial locations within theunfiltered wavefield, a space-variant velocity based on the coordinatelocation of the selected one of the plurality of spatial locationswithin the unfiltered wavefield; determining, by the computer in a sixthcomputer process, responsive to the space-variant velocity determined inthe fifth computer process, for the selected one of the plurality ofspatial locations within the unfiltered wavefield, a quotient of thetemporal frequency and the space-variant velocity of the selected one ofthe plurality of spatial locations, to thereby define a function k(x),wherein x is a selected one of the plurality of spatial locations andk(x) is a quotient of the temporal frequency and the space-variantvelocity of the selected one of the plurality of spatial locations;determining, by the computer in a seventh computer process, responsiveto determining the function k(x) in the sixth computer process, for theselected one of the plurality of spatial locations within the unfilteredwavefield, an exponential function of a product of (i) a square root ofnegative one, (ii) a preselected wavefield depth increment, and (iii) asquare root of (1) a square of the transverse wavenumber of the selectedone of the plurality of spatial locations subtracted from (2) a squareof the function k(x), to thereby define a multi-variable functionŴ(k_(x), k(x), Δz), wherein k_(x) is the transverse wavenumber of theselected one of the plurality of spatial locations, k(x) is a quotientof the temporal frequency and the space-variant velocity of the selectedone of the plurality of spatial locations and Δz is the preselectedwavefield depth increment; determining, by the computer in an eighthcomputer process, responsive to determining the multi-variable functionŴ(k_(x) , k(x), Δz) in the seventh computer process, for the selectedone of the plurality of spatial locations within the unfilteredwavefield, a product of (i) a quotient of one and a product of two andpi, and (ii) an integral over a set of real numbers, with respect to thetransverse wavenumber of the selected one of the of the plurality ofspatial locations, of a product of the multi-variable function Ŵ(k_(x) ,k(x), Δz) and an exponential function of: (1) a product of negativesquare root of negative one, (2) the transverse wavenumber of theselected one of the plurality of spatial locations, and (3) a differencebetween the coordinate location of the selected one of the plurality ofspatial locations and a coordinate location of a second one of theplurality of spatial locations where the second one of the plurality ofspatial locations is located at a point closer to a boundary of thesurface wave propagation zone than the selected one of the plurality ofspatial locations, to thereby define a multi-variable function W(x-x′,k(x), Δz) wherein x′ is the coordinate location of the second one of theplurality of spatial locations; determining, by the computer in a ninthcomputer process, responsive to determining the multi-variable functionW(x-x′, k(x), Δz) by the eighth computer process, a complex conjugate ofthe multi-variable function W(x-x′, k(x), Δz) to thereby define amulti-variable function W*(x-x′, k(x), Δz); and determining, by thecomputer in a tenth computer process, responsive to determining themulti-variable function W(x-x′, k(x), Δz) in the eighth computer processand determining the multi-variable function W*(x-x′, k(x), Δz) in theninth computer process, an integral over a set of real numbers, withrespect to the coordinate location of the selected one of the pluralityof spatial location, of a product of W(x-x′, k(x), Δz) and W*(x-x′,k(x), Δz) to thereby build a nonstationary convolution operator definedby a multi-variable function P(x-x′, k(x), Δz).
 6. The computerimplemented method of claim 5, wherein the step of extrapolating, by thecomputer in the third computer process the unfiltered wavefield at eachof the plurality of spatial locations of the unfiltered wavefield to adepth level below the surface wave propagation zone of the seismicenergy signals to thereby locally filter each of the plurality ofspatial locations of the unfiltered wavefield further includes the stepsof using, at each of the plurality of spatial locations, at least one ofthe plurality of nonstationary convolution operators built by thecomputer in the second computer process associated with that one of theplurality of spatial locations, and taking an integral over a set ofreal numbers of a product of the multi-variable function P(x-x′, k(x),Δz) and the unfiltered wavefield to thereby perform localized filteringof the selected one of the plurality of spatial locations.
 7. Thecomputer implemented method of claim 6, wherein the computer implementedmethod further includes the steps of: receiving from a seismic imagereceiver at a recording surface a plurality of seismic energy signalsthat have propagated throughout a surface wave propagation zone; andconverting the plurality of seismic energy signals received from theseismic energy receiver into unfiltered, unsorted seismic image data. 8.The computer implemented method of claim 4, wherein the step ofconstructing, by the computer in the first computer process theunfiltered pressure wavefield further includes the step of performing aFourier transformation of the unfiltered wavefield over a temporalcoordinate; wherein the computer implemented method further includes thestep of generating, by the computer in an eleventh computer process,filtered seismic image data for each of the plurality of spatiallocations of the unfiltered wavefield responsive to extrapolating, bythe computer in the third computer process the unfiltered wavefield ateach of the plurality of spatial locations of the unfiltered wavefield;and wherein the computer implemented method further includes the step ofconverting, by the computer in a twelfth computer process, the filteredseismic image data into a graphic image capable of being displayed onthe display adapted to be in communication with the computer.
 9. Thecomputer implemented method of claim 8, wherein the computer implementedmethod further includes the step of stabilizing, in a thirteenthcomputer process by the computer, each of the nonstationary convolutionoperators built by the computer in the second computer process for eachof the plurality of spatial locations of the unfiltered wavefield usinga weighted least squares with a transition band approach.
 10. A seismicimage filtering machine to create a filtered seismic image on a display,the seismic image filtering machine comprising: a first database storingunfiltered, unsorted seismic image data derived from a plurality ofseismic energy signals received from a seismic energy receiver at arecording surface after propagating throughout a surface wavepropagation zone; a computer adapted to be in communication with thefirst database and having at least a processor, memory, and a display;an unfiltered wavefield constructor computer readable program productstored in a tangible computer readable storage medium and includinginstructions that, when executed by the computer, cause the computer toperform the operation of constructing an unfiltered wavefield delineatedby a plurality of spatial locations from the unfiltered, unsortedseismic image data stored in the first database; a nonstationaryconvolution operator builder computer readable program product stored ina tangible computer readable storage medium and including instructionsthat, when executed by the computer, cause the computer to perform theoperation of building, responsive to the unfiltered wavefieldconstructer computer readable program product, a plurality ofnonstationary convolution operators, one for each of the plurality ofspatial locations of the unfiltered wavefield; a localized filtercomputer readable program product stored in a tangible computer readablestorage medium and including instructions that, when executed by thecomputer, cause the computer to perform the operation of locallyfiltering each of the plurality of spatial locations of the unfilteredwavefield using, at each spatial locations, at least one of theplurality of nonstationary convolutions operators associated with thatone of the plurality of spatial locations to thereby effectuate a singledownward extrapolation of the unfiltered wavefield; and a filteredseismic image creator computer readable program product stored in atangible computer readable storage medium and including instructionsthat, when executed by the computer, cause the computer to perform theoperation of creating, on the display, a filtered seismic imageresponsive to converting filtered seismic image data into a graphicimage form capable of being displayed on the display, the filteredseismic image data being generated responsive to filtering in thelocalized filter computer readable program product the unfilteredwavefield at each of the plurality of spatial locations of theunfiltered wavefield.
 11. The seismic image filtering machine of claim10, wherein each of the plurality of nonstationary convolution operatorsbuilt by the nonstationary convolution operator builder computerreadable program product is different from others of the plurality ofnonstationary convolution operators and is uniquely associated with oneof the plurality of spatial locations of the unfiltered wavefield;wherein the operation of filtering by the localized filter computerprogram product responsive to the nonstationary convolution operatorbuilder computer readable program product is implemented in one of, orboth, a seismic energy source domain or a seismic energy receiverdomain; wherein the propagation zone includes complex geology and ruggedtopography; and wherein the unfiltered wavefield includes coherentseismic noise in the form of evanescent waves that have propagatedthroughout the surface wave proposition zone in complicated wave pathsdue to the complex geology and rugged topography within the propagationzone.
 12. The seismic image filtering machine of claim 10, wherein thefiltered image creator is further responsive to filtered seismic imagedata generated by attenuating coherent seismic noise from surface wavesof an unfiltered wavefield constructed from unfiltered seismic imagedata through a single downward extrapolation of the unfiltered wavefieldusing a plurality of nonstationary convolution operators to performlocalized filtering at each of a plurality of spatial locations of anunfiltered wavefield.
 13. The seismic image filtering machine of claim10, wherein each of the nonstationary convolution operators being basedon a coordinate location of each of the plurality of spatial locationsof the unfiltered wavefield and the space-variant velocity, temporalfrequency, transverse wavenumber, and wavelength of the unfilteredwavefield at each spatial location.
 14. The seismic image filteringmachine of claim 10, wherein the nonstationary convolution operatorbuilder computer readable program product further includes instructionsthat when executed by the computer cause the computer to perform theoperations of: determining, for a selected one of the plurality ofspatial locations within the unfiltered wavefield, a space-variantvelocity; determining, for the selected one of the plurality of spatiallocations within the unfiltered wavefield, a quotient of a temporalfrequency and the space-variant velocity of the selected one of theplurality of spatial locations to thereby define a function k(x),wherein x is a selected one of the plurality of spatial locations andk(x) is a quotient of the temporal frequency and the space-variantvelocity of the selected one of the plurality of spatial locations;determining, for the selected one of the plurality of spatial locationswithin the unfiltered wavefield, an exponential function of a product of(i) a square root of negative one, (ii) a preselected wavefield depthincrement, and (iii) a square root of (1) a square of the transversewavenumber of the selected one of the plurality of spatial locationssubtracted from (2) a square of the function k(x), to thereby define amulti-variable function Ŵ(k_(x) , k(x), Δz), wherein k_(x) is thetransverse wavenumber of the selected one of the plurality of spatiallocations, k(x) is a quotient of the temporal frequency and thespace-variant velocity of the selected one of the plurality of spatiallocations and Δz is the preselected wavefield depth increment;determining, for the selected one of the plurality of spatial locationswithin the unfiltered wavefield, a product of (i) a quotient of one anda product of two and pi, and (ii) an integral over a set of realnumbers, with respect to the transverse wavenumber of the selected oneof the of the plurality of spatial locations, of a product of themulti-variable function Ŵ(k_(x) , k(x), Δz) and an exponential functionof: (1) a product of negative square root of negative one, (2) thetransverse wavenumber of the selected one of the plurality of spatiallocations, and (3) a difference between the coordinate location of theselected one of the plurality of spatial locations and a coordinatelocation of a second one of the plurality of spatial locations, tothereby define a multi-variable function W(x-x′, k(x), Δz), wherein x′is the coordinate location of the second one of the plurality of spatiallocations; and determining an integral over a set of real numbers, withrespect to the coordinate location of the selected one of the pluralityof spatial location, of a product of the multi-variable function W(x-x′,k(x), Δz) and a complex conjugate of the multi-variable function W(x-x′,k(x), Az) to thereby build a nonstationary convolution operator.
 15. Theseismic image filtering machine of claim 14, wherein the localizedfilter computer readable program product further includes instructionsthat when executed by the computer cause the computer to perform theoperation of downward continuing the unfiltered wavefield at each of theplurality of spatial locations of the unfiltered wavefield to a depthlevel below the surface wave propagation zone of the seismic energysignals.
 16. The seismic image filtering machine of claim 15, whereinthe unfiltered wavefield constructed by the unfiltered wavefieldconstructor computer readable program product has been Fouriertransformed over a temporal coordinate; and wherein the localized filtercomputer readable program product further includes instructions thatwhen executed by the computer cause the computer to perform theoperation of generating, for each of the plurality of spatial locationsof the unfiltered wavefield, filtered seismic image data responsive tofiltering each of the plurality of spatial locations.
 17. The seismicimage filtering machine of claim 16, wherein the seismic image filteringmachine further includes a nonstationary convolution operator stabilizercomputer readable program product stored in a tangible computer readablestorage medium and including instructions that, when executed by thecomputer, cause the computer to perform the operation of stabilizingeach of the nonstationary convolution operators using a weighted leastsquares with a transition band approach.
 18. A non-transitory computerreadable program product stored in a tangible computer readable storagemedium and including instructions that when executed by a computer causethe computer to perform the operations of: constructing an unfilteredwavefield delineated by a plurality of spatial locations fromunfiltered, unsorted seismic image data generated responsive to aplurality of seismic energy signals propagated through a surface wavepropagation zone and received from a seismic image receiver; building,for each of the plurality of spatial locations of the unfilteredwavefield, a plurality of nonstationary convolution operators, one foreach of the plurality of spatial locations of the unfiltered wavefield;filtering, in a space-frequency domain, each of the plurality of spatiallocations of the unfiltered wavefield using, at each of the plurality ofspatial locations, at least one of the plurality of nonstationaryconvolution operators associated with that one of the plurality ofspatial locations; and generating a filtered seismic image on one ormore output devices, each adapted to be in communication with thecomputer, responsive to each of the plurality of spatial locations ofthe unfiltered wavefield filtered in the space-frequency domain.
 19. Thecomputer readable program product of claim 18, wherein the operation offiltering in the space-frequency domain each of the plurality of spatiallocations of the unfiltered wavefield is performed through a singledownward extrapolation where the unfiltered wavefield at each of theplurality of spatial locations of the unfiltered wavefield isextrapolated to a depth level below the surface wave propagation zone ofthe seismic energy signals using the associated one of the plurality ofnonstationary convolution operators.
 20. The computer readable programproduct of claim 19, wherein each of the plurality of nonstationaryconvolution operators is different from others of the plurality ofnonstationary convolution operators and is uniquely associated with oneof the plurality of spatial locations of the unfiltered wavefield;wherein the operation of filtering, in the space-frequency domain, isimplemented in one of, or both, a seismic energy source domain or aseismic energy receiver domain; wherein the propagation zone includescomplex geology and rugged topography; and wherein the unfilteredwavefield includes coherent seismic noise in the form of evanescentwaves that have propagated throughout the surface wave proposition zonein complicated wave paths due to the complex geology and ruggedtopography within the propagation zone.
 21. The computer readableprogram product of claim 20, wherein each of the nonstationaryconvolution operators being based on a coordinate location of each ofthe plurality of spatial locations of the unfiltered wavefield and aspace-variant velocity, temporal frequency, transverse wavenumber, andwavelength of the unfiltered wavefield at each of the plurality ofspatial locations.
 22. The computer readable program product of claim21, wherein the computer readable program product further includinginstructions that, when executed by the computer, cause the computer toperform the operations of: performing a Fourier transformation of theunfiltered wavefield over a temporal coordinate; stabilizing each of thenonstationary convolution operators using a weighted least squares witha transition band approach; and generating filtered seismic image datafor each of the plurality of spatial locations of the unfilteredwavefield responsive to filtering, in the space-frequency domain, eachof the plurality of spatial locations of the unfiltered wavefield. 23.The computer readable program product of claim 22, wherein the computerreadable program product further including instructions that, whenexecuted by the computer, cause the computer to perform the operation ofconverting the filtered seismic image data into a graphic image capableof being transmitted by the computer to the one or more output devicesadapted to be in communication with the computer; and wherein the one ormore output devices adapted to be in communication with the computerinclude one or more of: a printer, a brail printer, a television, amonitor, a CRT monitor, an LCD monitor, a plasma monitor, an OLEDscreen, a DLP monitor, a video projection, and a three-dimensionalprojection, a touch screen.
 24. The computer readable program product ofclaim 23, wherein the operation of filtering, in a space-frequencydomain, each of the plurality of spatial locations of the unfilteredwavefield further includes instructions that, when executed by thecomputer, cause the computer to perform the operations of: determining,for a selected one of the plurality of spatial locations within theunfiltered wavefield, a space-variant velocity; determining, for theselected one of the plurality of spatial locations within the unfilteredwavefield, a quotient of a temporal frequency and the space-variantvelocity of the selected one of the plurality of spatial locations tothereby define a function k(x), wherein x is a selected one of theplurality of spatial locations and k(x) is a quotient of the temporalfrequency and the space-variant velocity of the selected one of theplurality of spatial locations; determining, for the selected one of theplurality of spatial locations within the unfiltered wavefield, anexponential function of a product of (i) a square root of negative one,(ii) a preselected wavefield depth increment, and (iii) a square root of(1) a square of the transverse wavenumber of the selected one of theplurality of spatial locations subtracted from (2) a square of thefunction k(x), to thereby define a multi-variable function Ŵ(k_(x) ,k(x), Δz), wherein k_(x) is the transverse wavenumber of the selectedone of the plurality of spatial locations, k(x) is a quotient of thetemporal frequency and the space-variant velocity of the selected one ofthe plurality of spatial locations and Δz is the preselected wavefielddepth increment; determining, for the selected one of the plurality ofspatial locations within the unfiltered wavefield, a product of (i) aquotient of one and a product of two and pi, and (ii) an integral over aset of real numbers, with respect to a transverse wavenumber of theselected one of the of the plurality of spatial locations, of a productof the multi-variable function Ŵ(k_(x) , k(x), Az) and an exponentialfunction of: (1) a product of negative square root of negative one, (2)the transverse wavenumber of the selected one of the plurality ofspatial locations, and (3) a difference between the coordinate locationof the selected one of the plurality of spatial locations and acoordinate location of a second one of the plurality of spatiallocations, to thereby define a multi-variable function W(x-x′, k(x),Δz), wherein x′ is the coordinate location of the second one of theplurality of spatial locations; and determining an integral over a setof real numbers, with respect to the coordinate location of the selectedone of the plurality of spatial location, of a product of themulti-variable function W(x-x′, k(x), Δz) and a complex conjugate of themulti-variable function W(x-x′, k(x), Δz) to thereby build anonstationary convolution operator.